{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "# Shading regions inside matplot chart using mplfinance\n",
    "\n",
    "## https://stackoverflow.com/questions/75572878/\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This allows multiple outputs from a single jupyter notebook cell:\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(252, 9)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>UpperB</th>\n",
       "      <th>LowerB</th>\n",
       "      <th>PercentB</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>132.089996</td>\n",
       "      <td>134.100006</td>\n",
       "      <td>131.779999</td>\n",
       "      <td>133.919998</td>\n",
       "      <td>117.161659</td>\n",
       "      <td>202385700</td>\n",
       "      <td>132.373927</td>\n",
       "      <td>125.316073</td>\n",
       "      <td>1.219057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-05</th>\n",
       "      <td>133.779999</td>\n",
       "      <td>134.080002</td>\n",
       "      <td>133.389999</td>\n",
       "      <td>133.809998</td>\n",
       "      <td>117.065437</td>\n",
       "      <td>165936000</td>\n",
       "      <td>133.254297</td>\n",
       "      <td>124.912703</td>\n",
       "      <td>1.066618</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2011-07-01  132.089996  134.100006  131.779999  133.919998  117.161659   \n",
       "2011-07-05  133.779999  134.080002  133.389999  133.809998  117.065437   \n",
       "\n",
       "               Volume      UpperB      LowerB  PercentB  \n",
       "Date                                                     \n",
       "2011-07-01  202385700  132.373927  125.316073  1.219057  \n",
       "2011-07-05  165936000  133.254297  124.912703  1.066618  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>UpperB</th>\n",
       "      <th>LowerB</th>\n",
       "      <th>PercentB</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-06-28</th>\n",
       "      <td>132.289993</td>\n",
       "      <td>132.990005</td>\n",
       "      <td>131.279999</td>\n",
       "      <td>132.789993</td>\n",
       "      <td>118.641281</td>\n",
       "      <td>169242100</td>\n",
       "      <td>136.500761</td>\n",
       "      <td>128.219241</td>\n",
       "      <td>0.551922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-06-29</th>\n",
       "      <td>135.199997</td>\n",
       "      <td>136.270004</td>\n",
       "      <td>134.850006</td>\n",
       "      <td>136.100006</td>\n",
       "      <td>121.598610</td>\n",
       "      <td>212250900</td>\n",
       "      <td>136.721010</td>\n",
       "      <td>128.792993</td>\n",
       "      <td>0.921670</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2012-06-28  132.289993  132.990005  131.279999  132.789993  118.641281   \n",
       "2012-06-29  135.199997  136.270004  134.850006  136.100006  121.598610   \n",
       "\n",
       "               Volume      UpperB      LowerB  PercentB  \n",
       "Date                                                     \n",
       "2012-06-28  169242100  136.500761  128.219241  0.551922  \n",
       "2012-06-29  212250900  136.721010  128.792993  0.921670  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)\n",
    "df.shape\n",
    "df.head(2)\n",
    "df.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "image/png": 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umz+fCUcfzdgjj+TEo4/mu8cdd8DrPfDLX7J1xw6eeOml0LarL7iA4fn5AKGLEK7GRs676aZQ4h0fF8cl3/8++bm5vPrBB6wtLgbg/735JiOHDuU3V1wBtI1rnz5rFi17kmaTycSU73yHY486ihqXiw+++KLLsu2feP/yJz/hTzfddHAzi1ssYXerqqoo3hM7QEJCAllZWe0+9cMPP2TUqFGcd955mM1mPB5Pl283ffr0sMR78ODBnH/++WRmZrJp0yZe26dXQWtrKz/4wQ9Cibfdbufiiy8mLy+P//73v6F9//jHPzJ27Fh++tOfRl5uidi4cZCY2ExeXqLRoUiUKyyElJRmRo3SsSIikVHyLR1btIjm118ncdAgoyMR6VBHiVJ33Pnzn/PK++9Tu6frcbPPx0dr1vDRmjWhfU4fP55Hb775kFqO99q6Y0dY0vnTc85p+3322aHku76xkZfee4//+/73I3pNa1ISf7z+eq574IHQtorqal5evpyXly8HwGa1cs2PfsQffv7zUBL+q0suYflnn4Ul3xedddYBXdbnv/46u2tqQvfn3X47Pzv/fKBtvP0xP/5xqNv8g889x63TpxMXF8f98+eHEm+AhXPmcOF+3aa37tjRYbmeX7KEWX/7WyjxvuPKK7nrmmsi+pu0x5WUxIMPPghATU0NCxcuDHU5BzjvvPNITGz/i/SJJ57If/7zH5IivCCyfv16XtnnIsv48eP5z3/+g81mC22rqqoiISEBgCVLlvC///0v9NiyZcv41re+Fbp/0UUX8cILLwBtCbiS756xaBG8/nozgwYpoZLO3X8/7NzZzLnn6lgRkchonW/p1K5uLt0k0tt2dJK4RarA4eCL55/nivPOI3WfxGhf761axXdmzKDM6Tzk93v6lVfCxgVfvCf5Pn38eBz7XEzoaEK2jsy86CJeffhhThk3rt1WYbfHw4P/7/9xye9/3+2YP1q7NnQ7Li6OSydPDt1PtFhCFxAAal0uNpaUAIRdZBhXWHhA4g2EWtnbc8e8eaHE+4Ff/vKQEm+A2tpabrnlFm655RbuvfdeSvbECXDkkUfy6D7zBOzvV7/6VcSJN8AHH3wQdv+3v/1tWOINbd3e09LSAA7omv7tb387bP3wvYk3wNq1a2loaIg4FukenfskUjpWRKQ7lHxLp5L3mZhJJBrtn8wcrCEDB/LU739Pzbvvsuof/2Durbcy7cwzSdynm3JdQwNPv/rqIb1Pa2srz77+euj+cSNHctTQoUBbUrtvcvr+55/zdTcvLkw59VQ+fPJJqt99lzcffZTZV13F+P3Gjr/03nvdXhO9pr4+dDsjNRXLntbavRz79UCo2dOavO/zhh1CL5q4uDiGHeYhMGazmYyMDE4++WQeeOAB1qxZw6BOYhw5cmS3Xr9mn54CAMOGDevW/l2pqqrq1v4SOZ37JFI6VkSkO9TtXDqVarcbHYJIp/a2Gh4u8fHxnFBUxAlFRfxi2jRWb9zICfvMkt7dpHV/b61cSXllZej+55s2tTvjOLTNmv30q69y9y9+0e33ybDbmXTyyUw6+WRmXXUV1/3xj/x5n5bT7bt2MaQb61ln7vN3rm1owOf3hyXgzurq8P331B2ZaWmh7uoHs8zZqGHD2FhSQmtrKz/57W/5t8XCud/5TrdfZ68hBQVs2779oJ7b3Qs9mZmZYfdLSko45phjItrfZDIxZ84c4juZyT0jI6Nb8Ujk7PZUo0OQGKFjRUS6Qy3f0rFp00i89Va49VajIxHpUHl5+SG/xh1/+QuvLF+Oz+8/4LHU/Vo1stLTD+m9utuVfP4bbxDYZzb2jpRXVjLz/vtZ38FyaPt3p8/aJ5nef6muJq/3gOefPHZs6HZrayv/eOON0P1mn48Fb70Vup9htzNqTyvvqcceG9q+priYl95994DX7iwpXzhnDscedRQA/pYWfnTrrSz75JMO9+/SPhc+etqp+y27NmfOHJqamsK21dTUUL+nd8App5wS2h4MBsnNzeVXv/rVAT8XXHABRx99NOmHeCxK+6ZNg1tvTdSpT7rU9hUpkWnTjI5ERGKFWr6lY2vWYC0vh/2+LIpEE/th6J3x0Zo13PP006SnpnLqsccyevhw7DYbu6qqeGHZsrB9v3/yyR2+zupNm8Jayfc1+6qr+Nbo0by+z7jeYYMG8a12lhPbtmsXn65bB7Qtx7V05UomdfK+AD6/n7mLFjF30SKOGjKEk8eOZcjAgZhMJr7csoWX3nsvtO/QvDyKjjgidD8/NzfstX77l7+wprgYS0ICxx51FGd861tMP/dc7n7qqdBs59fcey8r1q4NzXa+d7I1gJt++lPi4uIAuHX6dBYvX/7N2ty33cbU736XcYWF1Dc2suJ//8ORlcXLDz3UbrnsNhtL//xnTrnySopLS2n2+Zh6880seewxvnv88Z3+Tdr/Q/m6/5yDNHr0aKZOnRqadO2///0vRUVFodnOt2zZwiuvvML777/PuHHj+P73v8+YMWNYt+d/P2PGDF5++WWOPfZY4uPjKSsr49NPP2Xt2rVMnz6ds88+u9fK0p+sWQPl5Vad+qRLxcVQWWmlneu2IiLtUvItIjHtcCw1tlddQ0Nover2/PyHP+R7HXQRB2hsamL1xo3tPlZVV8c/3ngDf0tLaNs911zDT/aZqGyvUqeTYeedF2rxfvrVV7tMvve1eft2NnfQtdqamMhTv/td2IRsQwYOZHxREas2bADaWqjX7Fl+69pp0zjjW98iLSWFVx56iCk33kh1fT0tra08s88yWXv95Oyzuf3yy0P3TygqYv7s2cy4+248zc0Eg8GwGdgBpn73u52WJycjg2V/+QunXHklZRUVeJqbOffGG3n7z39mQifduKPB/Pnzw9b53r59e4eTusXFxfHKK6+E1vlubW0Nre0tIiIisU/Jt4jEtIqKCrKzsw/pNf7xhz/w7n//y/LVq1m3dSsVNTVU1dUBkJuZyQmjRjH93HM5r4sksSv7TtaWlZbGD08/vd39ChwOzj7xRJasWAHAqx98QFVdHdmddDMucDhY8fTTLF+9mg+/+IJtu3axu6aGusZGkpOSGDpwIKePH8/1F13EEe3MLv7vBx7gV488wnuffUZ1fX27Xd0nHHMM6194gccWLuTNjz9my44deJubyU5PZ3xREVdMncr5p512wPMunjSJE48+mrkvvMC7q1bx9c6dNPt8ZKWlcfSIEfx44sQu/nJt5Xt77ly+87OfUVVXR2NTE5Ouv553583j+FGjuny+UdLS0li+fDn//Oc/WbBgAZ9//jnV1dUkJSWRn5/PqaeeSv4+/48jjjiCNWvW8OSTT7J48WK+/PJL6urqSExMZPDgwRx77LGceeaZ/PCHPzSwVCIiInIwTMF917vpQnltJYNuubDL/Up+9xQfnDGFYCfjFE1mMxetXkHiPuMO3c4KXjzpNH60Yjk2R26Hz5VeMmgQlJdDTg4sWWJ0NCLt2rlzZ6czVIsAMGlS23jvvDw4iInfpP/QqU8ipWpFRLqrWy3fVksSZpOZQLDjpNpsMpOWncNFq1fQ4mmbtMdTWckbU6cx+ZVFWHNy2t7YmkRiWhrN9fVh++37e9/9RETak7DfklciIiIiItGoW8l3hi2VqkdepsnXlizvqq9h/N1Xs+qOJxiY1rZESrIliQxb27IL+yfN1pycsBbt5vp6/nX8SQe0kL8x9ZtpI9trIRcR2auyspIBAwYYHYaIiIhI1Jg3bx7z5s1j27ZtQNskoL///e+ZNGkSAE6nk1tuuYVly5bR0NDAUUcdxW9/+1suuOCC0GvU1NRw3XXX8dprr2E2m7ngggt49NFHSUlJMaJIfUK3x3xn2FJDyfVeA9MyGZSR0+03b/F4O+2aDhAMBGjxeJV8i0i7MrOyjA5BREREJKrk5+dz3333ceSRRxIMBpk/fz5Tp07liy++YPTo0Vx66aXU1dXx6quvkp2dzYIFC7jwwgv57LPPOHbPMqEXX3wxu3btYtmyZfj9fi6//HKuuuoqFixYYHDpYpfW+RYREREREelDpkyZwve//32OPPJICgsLueeee0hJSeGTTz4BYMWKFVx33XV861vf4ogjjuCOO+4gPT2d1atXA7Bx40beeustnnzySb797W9zyimn8Pjjj7Nw4ULKy8uNLFpMU/ItIjGtprra6BBEREREeoXL5Qr7aW5u7vI5ra2tLFy4ELfbzYQJEwA46aST+Ne//kVNTQ2BQICFCxfi9Xo5bc+qJStXriQ9PZ0T9lli9cwzz8RsNvPpp5/2SNn6g251O1+9ejU5eyZMq6iowJSSBMCatWuJGzmGxsZGamtrGTp0KDU1NbhcLoYPH07pnvViGxpcfF25G6/Xy6hRo9i4fn1E77t27RpOyPwea9euxWw2U1RUxLp160hISGDEiBFs3LiRpKQkCgoKKC4uxmaz4XA42Lp1K3a7nczMTLZt20ZGRgYpKSmUlZWRnZ2NxWKhvLyc3NzcUJny8vLw+XxUVVUxePDgDsvkdDpxu90UFhZSWloaKtOWLVvw+/2MGTOGDRs2EAgEGDt2LGvXrgVo93a0lin9Bz8grbQUb3IylevXM3z4cEpKSggEAhQWFlK85//a3m2z2cywYcPYunUr8fHxDB48mJKSEiyJiTgcDkq3b8dqtZKVlcWOHTuw2WykpaVRXl6O3W7HarVSUVFBeno6CQkJVFZWhroX11RXk5OTg9/vp66ujtzcXDweDy6Xi7y8POrr63G73eTn51NdXY3H46FgyBCcTie+5maGDRtGWVkZLS0tKlMfKFOTx8P69ev7VJn64v/J6DLFn3MO3vJyUiZMYOfmzf2qLleZulemH/zAxVdfJVFQkML69V9HdOxlZbXNe1NdXdPtz9OQIQU4nU6am32H/fOUmGjB4XCwfXtptz9PKlPXZTrttDSam20UFNSzatUufZ5Uph4rU1lZGWPGjAFg4MCBNDU1sdesWbOYPXs27fnyyy+ZMGECXq+XlJQUFi9eTFFREQAvvPACF110EVlZWcTHx5OcnMzixYsZMWIE0DYmfP85deLj48nMzMTpdLb7ftK1bi01tr+dtZXk33IhOx54odMx3x0tIbZ3e1e09JhBmprY9cILDDzySEhKMjoakXZpqTGJiNfLrq++YuCFF0JystHRSBRraoIXXtjFkUcO1KlPOuX1wldf7eLCCweqWpFe43K5wu4nJiaSmJjY7r4+n4/S0lLq6+t58cUXefLJJ3n//fcpKiriuuuu47///S9z5swhOzubl19+mT/96U98+OGHHH300cyZM4f58+ezefPmsNccMGAAd955J9dcc02PlbEv6/aEa/tKTUpm1pTppCapxumrXPX1DDQ6CJFO1NXVKfmWiKg+k0jV17tAR4tEQMeK9Da73R7xvhaLJdSSffzxx7Nq1SoeffRRfv3rX/PnP/+ZdevWMXr0aKCt5f/DDz9k7ty5PPHEEzgcDnbv3h32ei0tLdTU1OBwOA5fgfqZQxrzbbfamD31MuxW2+GKR6LM3mEGItFqb1cuka6oPpNI6ViRSOlYkVgSCARobm4OdVs3m8NTwbi4OAJ7VqKaMGECdXV1oQnYAN577z0CgQDf/va3ey/oPuaQWr6lj2towFtTAzk56nYuUcvj8RgdgsSCpqa2+qyhQd3OpVMNDVBT49WpT7rU1NR2rKhakWh0++23M2nSJAoKCmhoaGDBggUsX76cpUuXMnLkSEaMGMHPf/5zHnzwQbKysnj55ZdZtmwZr7/+OgCjRo3inHPOYcaMGTzxxBP4/X5mzpzJj3/8Y/Ly8gwuXexS8i0dO+448srL25LvJUuMjkakXfuPfRJp18UXk1dZCffeCzt3Gh2NRLHjjoPy8jyd+qRLF18MlZV5qlYkKu3evZtLL72UXbt2kZaWxjHHHMPSpUs566yzAHjzzTe57bbbmDJlCo2NjYwYMYL58+fz/e9/P/Qazz//PDNnzuSMM87AbDZzwQUX8NhjjxlVpD5BybeIxDRdfRUREREJ99RTT3X6+JFHHslLL73U6T6ZmZksWLDgcIbV72mdbxGJafX19UaHICIiIiLSJSXfIhLT3G630SGIiIiIiHRJybeIxLT8/HyjQxARERER6VKvJN8JNhtjr7+WBJuWJBORw6u6utroEEREREREutQrE65ZUlMYd8PM3ngrEelntNSYiIiIiMQCdTsXkZhWMGSI0SGIiIiIiHRJybeIxDSn02l0CCIiIiIiXVLyLSIxzdfcbHQIIiIiIiJd6pUx33JoXB43D7+9iJsmTsNu7XjSOl9DIxueepaiKy/Dkppy6G/8wgs0f/ghiTk5h/5aIj1k2LBhRocgseDee2murCTxO98xOhKJci+8AB9+2ExOTqLRoUiUu/deqKxs5jvf0bEiXTvs39MlJqnlOwY0eJu487X5NHibOt3P73az9rG5+A/XusfHHktZaiqMHHl4Xk+kB5SVlRkdgsSCkSPb6rNjjzU6Eolyxx4LqallOvVJl0aObDtWVK1IJCL9nu7yuJn9yrO4PIfp+7xEFSXfMa65vh63swK3swJPZSUAnsrK0Lbm+vpDev3WlpbDEaZIj2nRMSoRUn0mkWppaTU6BIkROlbkcIu00U1ik7qdx7Dm+nr+dfxJBAOBsO1vTJ0Wum0ym7lo9QoS09IO6j2GDB16KCGK9Ljhw4cbHYLECNVnEqmhQ7WKgkRGx4p0prm+nhaPFyCskWyveGvSQX9Hl9ik5DtK1bobaPK1fVh31deE/QZItiRh8XgPSLz3FwwEaPF4D+6DvWQJtW+8wcCRI+GMM7r/fJFeUFJSwqhRo4wOQ6Ldxx9Tu2kTA1ta4IILjI5GotiSJfDGG7WMHDlQpz7p1Mcfw6ZNtbS0DFS1IgfojUYyiT1KvqNQrbuB7BvOJxAM/7COv/vq0G2zyUzZ7X/r2UCuv56B5eWQk6PkW6JWoIsLUCIAPPggAysrYelSJd/Sqeuvh/LygTr1SZcefBAqKweqWpF2tfR0I5nEJI35jkJNPu8Biff+AsEAHr+WWBIpLCw0OgQRERERkS4p+RaRmFZcXGx0CCIiIiIiXVLyLSIiIiIiItLDlHyLSExTt3MRERGJNvHWJEzmzlMtk9lMvDWplyKSaKAJ10QkphUXFzN69GijwxAREZF+yOVx8/Dbi7hp4jTsVltoe2JaGhetXhG21NgbU6cx+ZVFWHNyAC011h8p+RYRERERETkIDd4m7nxtPjNOnRyWfENbAr5/cm3NycHmyA3bFskSwxm21J4IX3qZkm8RiWnqdi4iIiKxKpIlhlMSk2mY+0ZvhyY9QMm3iMQ0dTsXERGR3nQ4W6ojXWJY+gYl39KxlBRaExOJs1qNjkSkQ+YuJjMRAcBqbavPUlKMjkSiXEoKJCa2YrXGGR2KRDmrte1YSUnRsdKfRNJSbTaZqXrk5YgS8GRLEmaTudME22zSd52+Qsm3dOyLL/AvW0ZcdrbRkYh0aNiwYUaHILFgwQL8VVXEnXWW0ZFIlPviC1i2zE92thIq6dyCBVBV5eess3Ss9CeRtlQ3+bwRJd8ZtlSqHnk5rCV9/N1Xs+qOJxiYlgm0JejSNxh6GeVgp+D3NTSy5pE/42to7MnwBNi+bZvRIYh0auvWrUaHIDFC9ZlEatu27UaHIDFCx4ocDhm2VAZl5DAoIyeUcA9Mywxt02RrfYehyffeKfh/tGI5P1qxnMmvLAJg8iuLQtsuWr3igFkC/W43ax+bi9/tNiLsfiUuXp0jJLrF6xiVCKk+k0jFx6slUyKjY0Wi1bx58zjmmGOw2+3Y7XYmTJjAkiVLwvZZuXIlp59+OjabDbvdzqmnnorH4wk9XlNTw8UXX4zdbic9PZ0rr7ySxkY1fh4Kw7+JRDoFvxhjUF6e0SGIdGrw4MFGhyAxQvWZRCovb5DRIUiM0LEih1tqUjKzpkwnNSn5kF4nPz+f++67jyOPPJJgMMj8+fOZOnUqX3zxBaNHj2blypWcc8453H777Tz++OPEx8ezdu3asLl0Lr74Ynbt2sWyZcvw+/1cfvnlXHXVVSxYsOBQi9lvGZ58SxT7zW9o/vRTrMOGwc03Gx2NSLtKSko027l0be5cmktKsL7/PjzyiNHRSBT7zW/g00+bGTbMqlOfdGruXCgpaeb9962qVuSwsVttzJ562SG/zpQpU8Lu33PPPcybN49PPvmE0aNHc+ONN3L99ddz2223hfY56qijQrc3btzIW2+9xapVqzjhhBMAePzxx/n+97/Pgw8+SJ4uaB+UqJo6L8FmY+z115Jgs3W9cwea6+txOytwOyuo2/o1/737Puq2fh3a1lxffxgj7uMWLSL9k0/gnXeMjkSkQ5bERKNDkFjwzjtt9dmiRUZHIlFu0SL45JN0nfqkS++803asqFqR3uRyucJ+mpubu3xOa2srCxcuxO12M2HCBHbv3s2nn37KgAEDOOmkk8jNzeW73/0uH330Ueg5K1euJD09PZR4A5x55pmYzWY+/fTTHilbf9Ctlu/Vq1eTk5MDQEVFBXl5efh8Pqqqqhg8eDCNjY3U1tYydOhQampqcLlcDB8+HKfTidvtprCwkNLSUrxeL6NGjWLLli34/X7GjBnDhg0bCAQCjP3FVaxduxaAsWPHHnDbbDYzNKtt9u0N69czKsXGxo0bSUpKwpGezpunnQ3BYFjcG5+e/80ds5mj/j6X3KFDsFgslJeXk5ub27Nlaqcc+5epqKiIdevWkZCQQFaeA7PJRGC/cuzLbDKxdXNxRP83p9OJ2dPU7TId5fdjAfwtLRSvX8/w4cMpKSkhEAhQWFhIcXHb+7d322w2M2zYMLZu3Up8fDyDBw+mpKQES2IiDoeD0u3bsVqtZGVlsWPHDmw2G2lpaZSXl2O327FarVRUVJCenk5CQgKVlZVkZmUBUFNdTU5ODn6/n7q6OnJzc/F4PLhcLvLy8qivr8ftdpOfn091dTUej4eCIUNwOp34mpsZNmwYZWVltLS0qEx9oEyNjY2sX7++T5WpL/6fjC5Temsr8UBrIMCWzZt7pS4fMWJE6PxUUFBAcXExNpsNh8PB1q1bsdvtZGZmsm3bNjIyMkhJSaGsrIzs7OyoPT/1hzL5/VbAQiAQYP36jREde1lZbRMkVVfXdPvzNGRIAU6nk+Zm32H/PCUmWnA4HGzfXtrtz5PK1HWZ/P4jgAT8fh+rVq3V56mflGnNnv27UlpaBk2+UJmaK6uAg/teXlZWxpgxYwAYOHAgTU1NofeZNWsWs2fPbjeGL7/8kgkTJuD1eklJSWHx4sUUFRXxySefADB79mwefPBBxo0bxz/+8Q/OOOMM1q1bx5FHHonT6WTAgAFhrxcfH09mZiZOpzOiv4EcyBQMdpLhRZHm+npaPG1T8HsqK3lj6jQmv7II656LAfHWJFo8Xl486bQuX+tHK5ZH/ZjyWndDl0sOWBqaera8gwZBeTnk5MB+EzSIRIv169er27l0bdIkqKyEvDzYudPoaCSK6dQnkVK10j/trK0k/5YLu9xvxwMvMCgjJ3Tf7azgxZNOO+Q8xOVyhd1PTEwksYNegD6fj9LSUurr63nxxRd58sknef/996mrq+Pkk0/m9ttvZ86cOaH9jznmGCZPnsy9997LnDlzmD9/Pps3bw57zQEDBnDnnXdyzTXXHHQZ+rOYGPPdXF/Pv44/iWAgfE29N6ZOC902mc1MWfJyL0d2aFweNw+/vYibJk7Dbg3vap9hSz1gWYG9Sw7s5W5oQqS/s1qtRocgIiIi0ivsdnvE+1osFkaMGAHA8ccfz6pVq3j00UdD47yLiorC9h81ahSlpaUAOBwOdu/eHfZ4S0sLNTU1OByOQylCvxZVY7470uLxHpB47y8YCNDq7XrMQzRp8DZx52vzafAqiRY5WFl7uhqLiIiISMcCgQDNzc0MHTqUvLy8A1q1i4uLGTJkCAATJkygrq6O1atXhx5/7733CAQCfPvb3+7VuPuSmGj57u8O15IDIn3Rjh07SNtvuUIRERGRaHI4Jpbujttvv51JkyZRUFBAQ0MDCxYsYPny5SxduhSTycQtt9zCrFmzGDt2LOPGjWP+/Pls2rSJF198EWhrBT/nnHOYMWMGTzzxBH6/n5kzZ/LjH/9YM50fAiXfMeBwLTkQK1w+Lw+vfZ+bxn4XuyXJ6HAkytl66SQmIiIicrAsqSmMu2Fmr73f7t27ufTSS9m1axdpaWkcc8wxLF26lLPOOguAG264Aa/Xy4033khNTQ1jx45l2bJlDB8+PPQazz//PDNnzuSMM87AbDZzwQUX8Nhjj/VaGfoiJd8SdRp8zdz52TJmjDpRybd0Sa3eIiIiIuGeeuqpLve57bbbwtb53l9mZiYLFiw4nGH1ezEx5ltEpCPl5eVGhyAiIiIi0iW1fPey/ZcQ2/c3tC0htv8s54Y55xw8a9diHTTI6EhEOtSdWT+lH5swAc/OnVjHjjU6Eoly55wDa9d6GDRIKylI5yZMgJ07PYwdq2NFRCITE8l3vDUJk9nc6YznJrOZuKT217iLFrXuBrJvOJ9AMLwc4+++OnTbbDJT9cjL0ZGAP/44npdfxrpn1kORaKSlxiQiv/41nu3bsZ5/vtGRSJR7/HF4+WUPQ4aobpHO/frXsH27h/PP17HSnyRbkjCbzAd8n9+X2WQmWUMnpR0xkXwnpqVx0eoVtHjaWow9lZW8MXUak19ZhDWnbd3reGtS6PFo1eTzdvpBBQgEAzT5vNGRfAOVlZVkKvmWKFZRUUF2drbRYUgMqKysJNPoICQmVFZWMmSIjhbpWmVlJahm6VcybKlUPfJyWE/W8Xdfzao7nmBgWtuxEFU9WSWqxETyDW0JeOJ+EytZc3KwOXJD96M9+Y5Fdk1mJVEuPT3d6BAkRqg+k0ilpWk4i0RGx0r/lGFLPSC5HpiWyaCMHIMiklgRM8l3tNt3LHeDt4m/ffA6V516bmht7ljtehIfr0NEoltCQoLRIUiMUH0mkdKxIpHSsSIi3aEa4zDoaCz3n5a9GLptNpn53+yup/yPKqecQvrXX4PDAc8/b3Q0Iu2qrKxkwIABRoch0e7KK0l3OuHhh+Hzz42ORqLYKafA11+n69QnXbrySnA601WtiEjElHwfBpGO5fb4m3sposOkooKE+nqwWIyORKRDmVlZRocgsaCmpq0+q6gwOhKJchUVUF+foFOfdKmmpu1YUbUiIpHSOt+9yJpgwWzq/E+u2REj42tqYs0LL+FrajI6FBERERHpp1KTkpk1ZXpoqKlIZ9Ty3YvSk1OiYnZEl8fNw28v4qaJ07BbbT36Xj3F7/GydtFijjzje1iSVdn1ZzXV1Qx0OIwOQ0RERPohu9XG7KmXGR2GxAgl373MqNkR950Qbld9DXe+Np9zx07QkggS83JyNLOoiIiIiEQ/Jd/9QK2nkSG/++kB49LH33116LbZZKbqkZeVgEvM8fv9RocgIiIiItIljfnuBzx+X0QTwu1tGReJJXV1dUaHICIiIiLSJSXfIhLTcnNzjQ5BRERERKRLSr5FJKZ5PB6jQxARERER6ZLGfEvM8DU20uptWyvdu6ersbe2FnMwGNonLikRS0qKEeGJQVwul9EhiIiIiIh0Scm3dOzuu2n65BOSo2AZJ19jI2//3+UEA22JdhBIiovn45tuxbTPfiaziYnPPRNKwH1NTWx4fQlF507SkmR9VF5entEhSCy45hqanE6STzzR6Egkyt19N3zySRMOh84Z0rlrrgGns4kTT9SxcjD6wtK3It2lbucGSk1KZtaU6aQmRWmlfdFFVJ9wAkycaHQktHqbQ4k3gAlIbm0JS7wBgoFgqHUcvlkP3O/RZHJ9VX19vdEhSCyYOLGtPrvoIqMjkSh30UVwwgnV0XDqkyg3cWLbsaJq5eA0eJu487X5NHibjA5FpNeo5dtAdquN2VMvMzqMTjU1qUKU6OZ2u40OQWKE6jOJlI4ViZSOFRHpDrV8S6cGDhxodAgincrPzzc6BIkRqs8kUjpWJFI6VkSkO5R8S8eKi2lcvx5KS42ORKRD1dXVRocgsaC0tK0+Ky42OhKJcsXFsH59o0590qXS0rZjRdWKiERK3c6lY5Mnk1deDjk5sGRJj72Ny+PG6/eF7lc1tc1eXdVYR0IgAIDJq+WkpH1aakwi8stfkldZCU8+CTt3Gh2NRLHJk6G8PK+nT33SB/zyl1BZmadqRUQipuQ7hsVbkzCZzQT3JKjtMZnNxCUl9mJU3ePyuDnjoZsJ7LNcWKsJHFYL05+cQ9yezWm+IDcaFKNEt4IhQ4wOQURERESkS0q+Y1hiWhoXrV5By56ZvD2VlbwxdRqTX1mENScHaEvQqwK+zl7GUF6/LyzxBogLQl5TeMwBOr7AIP2b0+kkdcQIo8MQEREREelUnxrzvbcluDMms5l4a1IvRdTzEtPSsDlysTlyQwm3NScntC0xLc3gCEV6lq+5ueudRERERPqRefPmccwxx2C327Hb7UyYMIEl7YylCQaDTJo0CZPJxMsvvxz2WGlpKZMnTyY5OZkBAwZwyy230NLS0ksl6Jv6VMt3pC3BfTUhTbDZGHv9tSTYbEaHErGkBAtmk+mAbucVVgu5Hl+o27m5b10nksNo2LBhRocgIiIiElXy8/O57777OPLIIwkGg8yfP5+pU6fyxRdfMHr06NB+jzzyCCaT6YDnt7a2MnnyZBwOBytWrGDXrl1ceumlJCQkMGfOnN4sSp/Sp5JvaEvA90+u97YE93WW1BTG3TDT6DC6xW618e7ND4VNuLarycW4xY/z1sW/YmCyHQCTy80nv7jBoCglmpWVlXHUUUcZHYaIiIj0AJfHzcNvL+KmidOwW2OngcloU6ZMCbt/zz33MG/ePD755JNQ8r1mzRoeeughPvvsswOWzXv77bfZsGED77zzDrm5uYwbN4677rqLW2+9ldmzZ2OxWHqtLH2JmhPFcHarjQH2jNBPdko6ANkp6aFtKUlWY4OUqKXuTyIiIn1Xg7eJO1+bT4O3qdP9XB43s195FpfH3UuRGcPlcoX9NEcw/K61tZWFCxfidruZMGECAE1NTfz0pz9l7ty5OByOA56zcuVKjj76aHJzv2nAPPvss3G5XKxfv/7wFaif6VbL9+rVq8nZ0327oqKCvLw8fD4fVVVVDB48mMbGRmpraxk6dCg1NTW4XC6GDx+O0+nE7XZTWFhIaWkpXq+XUaNGsWXLFvx+P2PGjGHDhg0EAgHGjh3L2rVrAdq9bTabObKggOwfnc+mr7dyVIqNjRs3kpSUREFBAcXFxdhsNhwOB5vWrgGgprqaDWWlZGRkkJKSQllZGdnZ2VgsFsrLy0MH1cGWaeOmTRH9/dasXUvOSae2W6aioiLWrVtHQkICI0aM6LBMW7duxW63k5mZybZt2yIqkyklsjHuxcVfUW7eFvo/HeX3YwH8LS0Ur1/P8OHDKSkpIRAIUFhYSPGehS3bu202mxk2bBhbt24lPj6ewYMHU1JSgiUxEYfDQen27VitVrKystixYwc2m420tDTKy8tpSmi7JrS5eDPkDiIhIYFdW7dGVAaAHTt24Ktwkp+fT/mehVrdTW7Ka2vwNTczbNgwysrKaGlp6bUy2e12rFYrFRUVpKenk5CQQGVlJZlZWUDbMZqTk4Pf76euro7c3Fw8Hg8ul4u8vDzq6+txu93k5+dTXV2Nx+OhYMgQnE5nvy9Ta2sr69ev71Nl6ov/J6PLlN7aSjzQGgiwZfPmHjs/9WRdbtQ5t7+Vye+3AhYCgQDr12+M6NjLysoEoLq6ptufpyFDCnA6nTQ3+w775ykx0YLD4WD79tJuf55Upq7L5PcfASTg9/tYtWqtPk/dLFPznixkzdq1+IYM77BMpVUVAOyurMRTXd9hmUp2l3Pna/M5ZcBw0uKT+lS9V1ZWxpgxYwAYOHAgTU3fXIiYNWsWs2fPpj1ffvklEyZMwOv1kpKSwuLFiykqKgLgxhtv5KSTTmLq1KntPtfpdIYl3kDovtPpbPc50jVTMLjfVNN9iNtZwYsnncaPVizv0W7nO2sryb/lwi732/HACwzKyOmxODpS624g+4bzCQQ7njHcbDJT9cjLZNhSv9k4aBD0wjrf+9vZWE/+/7uLHZf8jkEpbUMIPFXVvHPFzyN6/plP/xVrdtuXcHd1DS9efT0/euIxbHtOutK3bNy4kVGjRhkdhkS7SZOgshLy8rQgr3TKoFOfxCBVK4dm7/fnrr4fH+79Yp3L5Qq7n5iYSGJi+8sK+3w+SktLqa+v58UXX+TJJ5/k/fffZ8uWLdx888188cUXpKSkAGAymVi8eDHnn38+AFdddRXbt29n6dKloddramrCZrPx5ptvMmnSpJ4pYB/X58Z8y4EybKlUPfIyTb62ieh21dcw/u6rWXXHEwxMa0tIky1J4Ym3SIwIdLLOvYiIiEhfYrfbI97XYrEwYs9yrMcffzyrVq3i0UcfxWq1snXrVtLT08P2v+CCC/jOd77D8uXLcTgc/Pe//w17vKKirRdCe93UOxMMBtm+fTtVVVUAZGdnM2TIkHYneuvrlHz3Exm21AOS64FpmZ1fGfzgA/wffEBCZu+2GKdaEpl1wlmkWtq/iieyr8LCQqNDkFjw97/jr6kh4dRTjY5EotwHH8AHH/jJzEwwOhSJcn//O9TU+Dn1VB0rh1utuyGs0Wjf36BGo4MVCARobm7mzjvv5Gc/+1nYY0cffTR/+tOfQhO1TZgwgXvuuYfdu3czYMAAAJYtW4bdbg91Xe9MXV0dCxYsYPHixXz66ae43eFj8W02G9/+9rf54Q9/yE9+8pMDLgT0VUq++6HUpGRmTZlOalJy5zsOHMjXLhdH9XJyY7ckMXv82b36nhK7iouLw5bMEGlXdjZfb9vGUfvN5iqyv4EDweX6msJCraIgncvOhm3bvmbgQB0rh1NHwyXH33116Ha7wyUlzO23386kSZMoKCigoaGBBQsWsHz5cpYuXYrD4Wi39bqgoCC0hOvEiRMpKirikksu4Y9//CNOp5M77riDa6+9tsNu7gDl5eXcc889PP300/h8basZtTfKubGxkffee4/33nuPm2++mSuvvJLbb7+dvLy8w/QXiE5Kvvshu9XG7KmXGR2GiIiIiEiYJp+303mKAALBQKhlXC3k7du9ezeXXnopu3btIi0tjWOOOYalS5dy1llnRfT8uLg4Xn/9da655homTJiAzWZj+vTp/OEPf+j0eSNGjKC5uTmUcGdkZHDssccyYsQIMjIyCAaD1NbWsmXLFtasWUNtbS1er5e//OUvPP300we0kPc1fTr5TrDZGHv9tSTYtCbgwTriiCOMDqHb/O5vZoD01tW1/a6txbzPVbe4pEQseyaYkNimbucSqVisz8QYOlYkUjpWjFPX1EjBr3+sFvIOPPXUU93av73W6SFDhvDmm29263W8Xi95eXlMnz6dH/7whxx//PGd7r969Wr+/e9/8+yzz/aLWdT7dPJtSU1h3A0zjQ4jdj39NLXvvMOAwkK46CKjo4nY+7+8CQJtFUgQSIqL5+ObbmXfKR1MZhMTn3tGCXgfoG7nEpFXXqG2uJgB27fDTJ0XpGNPPw3vvFNLYeGAWDr1iQFeeQWKi2vZvn2AqpXDKNmShNlk7nKVHjBF3ELeH5Nvozz33HNceOGFxMdHlmYef/zxHH/88dx555288MILPRyd8fp08i2H6N57GbB3vZVY+gYS+ObKnQlIbm05YJdgIEirtxmUfIv0D88+y4DKSli1Ssm3dOree6G8fEDMnfqk9z37LFRWDlC1cphFukoPEFGSvndf6R0//elPD+p58fHxB/3cWKLkW0Rimrqdi4iI9C2RrtKjpXQl1piNDkAkGviamljzwkv4mpq63lmiSnFxsdEhiIiIiAEybKkMyshhUEZOKOHem6QPyshR4m2gjRs38sEHH7B27drQtubmZn7zm98wYsQIUlNTGTduHPPnzzcwyt6n5FsE8Hu8rF20GL/Ha3Qo0k1ms6oxERERkWgybdo0vve97/HPf/4ztO0Xv/gF999/PyUlJbjdbv73v/9xxRVX8Le//c3ASHuXvrUeBnsnhuiMxpyI9Iy961GKiIhIdKt1N7CztpKdtZVhS4Pt3VbrbjA4Qjkcampq2LBhAwA//OEPgbalz/7xj38AYLfbmTZtGgMGDCAYDDJv3jzDYu1tGvN9GEQ6MYS6vogcflu3btVs5yIiIlGu1t1A9g3na2mwfuCrr74K3R45ciQA7733Hq2trZhMJh566CGuuOIK/v3vf/OjH/2IzZs3GxVqr1PyfZhEOjGERI+u1gPXWuCxIdKlLERERKTnuTxuHn57ETdNnIbdagttb/J5e3RpsNSkZGZNmU5qUnK3nyuHj9lsxmQyYTKZCAaDZGRkhB4zmdoW/p0xYwYzZswIbW9ubiYuLg6A1tbW3g24l+lbq8SEuKRETGYTwX2WEWuXqe2DHdxnnW9PXDzW1pawdb4xwQe/vClsv/3XA9da4LFh8ODBRocgIiLSr9W6G8J6gN752nzOHTvhgKXBepLdamP21Mt6/H2kc08//TSlpaXMnj0bk8nEvHnzSExM5IEHHmDDhg3YbDb+/Oc/A7Bp0ybuv/9+EhIS+Otf/2pw5L1DybfEBEtKChOfe6Ztbe5OxCUlAoT283u8bH73Pxx1xvdIsH5T8fub3Lw/86bQ/fbWA9da4LGhpKRE3c5FREQMEml38v/Nfqq3QxMDXHbZZdTV1TF79mwAPvroI4qKivjqq68wmUyceuqpTJ8+HYCFCxcCkJeXF9rW1yn5lo6NGIEvGMQycKDRkQBtCXjEifCe/azA+Mv+78DHqw5fXGIsS2Ki0SFILBg8GF98PJYRI4yORKLciBEQDPoYONBidCgS5QYPhvh4HyNG9O9jJdLu5B5/5w0o0nekp6fzgx/8gMWLF/P8888DEAwGMZlM/OIXvwjt9/bbb2MymTj66KONCrXXKfmWji1Zgm/JEiwOh9GRiHTIoeNTIvHYY/icTiyTJhkdiUS5JUtgyRIfDkf/Tqika489Bk6nj0mTdKyI7O/vf/87CQkJLF68GL/fT0ZGBrNmzWLy5MlA2+zn//znPwkGg/zkJz8xONreo+RbOrVzxw6OUnIjUax0+3Z1O5eI7Nyxg6OMDkJiwo4dO3E4dLRI13bs2AmqWXqUJlKLTZmZmSxcuJDW1lZqa2vJzs4Oezw1NZVNmzYBkJ+fb0SIhtA639KppCStTR5LfE1NrHnhJXxNTV3v3EdYrVajQ5AYofpMIqVjRSKlY6Xn7Z1Ibd+Z0yV2xMXFHZB4Q9v3tyFDhjBkyJDQTOf9gZJv6dS+ywNI9PN7vKxdtBi/x2t0KL0mKyvL6BAkRqg+k0jpWJFI6VgRCefxeAx5bqxQ8i0du/xy4n7/e7jzTqMjEenQjh07jA5BYsGdd7bVZ5dfbnQkEuUuvxx+//s4nfqkS3fe2XasqFoR+UZ+fj633XYbX331VcTP2bp1K7fddlu/WD5WY76lYx99hK28HGpqjI5EpEM2m7qhSQTWrMFWWQkNDUZHIlHuo4+gvNymU590ac0aqKy0qVoR2UdtbS0PPPAADzzwAKNHj2bixIkcd9xxjBgxgoyMDILBILW1tWzZsoXPP/+cd955h3Xr1hkddq9R8t0DNDGESO9JS0szOgQRERHpgjXBgtlk7nRZMrPJTLJF4+hj2f33388DDzxAVVUV69atY/369Z3uHwwGAcjOzubXv/51b4RoKCXfPWDvxBAi0vPKy8s15k5ERCTKpSenUPXIyzT52ual2VVfw/i7r2bVHU8wMC0TgGRLEhm2VCPDlEN0yy238Itf/IJnnnmGZ599ls8//7zT/Y8//nguv/xypk+f3i96Myr5FpGYZrfbjQ5BREREIpBhSw0l13t7ihbm5msm8z7GZrMxc+ZMZs6cSVlZGR9//DEbN26kqqoKaGvlHjVqFCeffHK/GOe9LyXfIhLTtNSYiIhI7FFP0f5h8ODB/PjHPzY6jKih2c5FJKZVVFQYHYKIiIiISJeUfItITEtPTzc6BBERERGRLin5FpGYlpCQYHQIIiIiIiJdUvItIjGtsrLS6BBERERERLqk5Fs6dvnlNJ19NkyZYnQkIh3KzMoyOgSJBVOmtNVnl19udCQS5S6/HM4+u0mnPunSlCltx4qqFYlG8+bN45hjjsFut2O325kwYQJLliwBoKamhuuuu46jjjoKq9VKQUEB119/PfX19WGvUVpayuTJk0lOTmbAgAHccssttLS0GFGcPkOznUvHfvMbGl98keThw42ORETk0FxxBY1bt5L8ox8ZHYlEud/8Bl58sZHhw5ONDkWi3BVXwNatjfzoRzpWJPrk5+dz3333ceSRRxIMBpk/fz5Tp07liy++IBgMUl5ezoMPPkhRURHbt2/n6quvpry8nBdffBGA1tZWJk+ejMPhYMWKFezatYtLL72UhIQE5syZY3DpYpeSb+lUbW0tA4wOQqQTNdXVDHQ4jA5DYoDqM4lUbW0t6GiRCOhYkWg1Zb/uO/fccw/z5s3jk08+4corr+Sll14KPTZ8+HDuuece/u///o+Wlhbi4+N5++232bBhA++88w65ubmMGzeOu+66i1tvvZXZs2djsVi6HdMXX3zBxo0bcbvdzJgx45DLGIvU7Vw6pS69Eu1ycnKMDkFihOoziVRWVqbRIUiM0LEivc3lcoX9NDc3d/mc1tZWFi5ciNvtZsKECe3uU19fj91uJz6+rW125cqVHH300eTm5ob2Ofvss3G5XKxfv75bMX/22WccffTRnHDCCVxyySVcc801eL1eMjMziY+PZ/ny5d16vVjWrZbv1atXh77oVlRUkJeXh8/no6qqisGDB9PY2EhtbS1Dhw6lpqYGl8vF8OHDcTqduN1uCgsLKS0txev1MmrUKLZs2YLf72fMmDFs2LCBQCDA2LFjWbt2LUC7t81mM0VFRaxbt46EhARGjBjBxo0bSUpKoqCggOLiYmw2Gw6Hg61bt2K328nMzGTbtm1kZGSQkpJCWVkZ2dnZWCwWysvLQweVyhReJl9dHTlNTRQXF+OPi2P48OGUlJQQCAQoLCykuLgYoN3bZrOZYcOGsXXrVuLj4xk8eDAlJSVYEhNxOByUbt+O1WolKyuLHTt2YLPZSEtLo7y8HLvdjtVqpaKigvT0dBISEqisrAx9ca6priYnJwe/309dXR25ubl4PB5cLhd5eXnU19fjdrvJz8+nuroaj8dDwZAhOJ1OfM3NDBs2jJKvv47omC/+qpiitBNiokxlZWU01dQCsGXLV8Q7U2L+/1RWVkZLS0unx15JSQmVlZV9qkx98f9kdJm8dXXsLi2FykpqvN5+VZerTN0r0//+t4WKikQyMy1s3RrZsbc3Aauurun252nIkAKcTifNzb7D/nlKTLTgcDjYvr20258nlanrMrndrUAqX3zxORZLa7/9PKXlRdbyv2btWhoHDo6JMkXb/6msrIwxY8YAMHDgQJqamkJ/11mzZjF79ux2/+ZffvklEyZMwOv1kpKSwuLFiykqKjpgv6qqKu666y6uuuqq0Dan0xmWeAOh+06nM6L/OcCmTZs4/fTTcbvdBIPB0PakpCTOP/98nn32WRYtWsRpp50W8WvGMlNw37+CyL4GDYLycsjJgT0TNPQVnqpq3rni513ud+bTf8WaHTutZe7qGl68+np+9MRj2PrJ1fj169czevRoo8OQaDdpElRWQl4e7NxpdDQSxfrwqU8OM1UrbXbWVpJ/y4Vd7rfjgRcYlKHeaofK5XKF3U9MTCQxMbHdfX0+H6WlpdTX1/Piiy/y5JNP8v7774cl4C6Xi7POOovMzExeffXV0BKuV111Fdu3b2fp0qWhfZuamrDZbLz55ptMmjQponh//OMf88ILLxAXF8e3vvUtVq5ciclkorW1lb/+9a9cc801HH300aGLIH2dxnyLSEzb/6qsiIiISF9lt9sj3tdisTBixAgAjj/+eFatWsWjjz7KX//6VwAaGho455xzSE1NZfHixaHEG8DhcPDf//437PUqKipCj0XqP//5DyaTiXvvvZcJEybwne98J/TY0KFDAdixY0fErxfrNOZbRGKax+MxOgQRERGRqBcIBEJjxF0uFxMnTsRisfDqq6+SlJQUtu+ECRP48ssv2b17d2jbsmXLsNvt7XZd78je5cuOPfbYAx7z+/0AYd3o+zq1fIvEOF9jI63etorUW1fX9ru2FvOeESVxSYlYUlKMCq/H7d/9SkRERKS/u/3225k0aRIFBQU0NDSwYMECli9fztKlS0OJd1NTE88991xo8jZom8g2Li6OiRMnUlRUxCWXXMIf//hHnE4nd9xxB9dee22H3dzb43A4KCsr4+233+a8884Le2zRokVA27Jo/YWSb5EY4PJ5eXjt+9w09rvYLd9cmfQ1NvL2/11OMNCWaAeBpLh4Pr7pVkx79jGZTUx87pk+m4Dn5eUZHYKIiIhIVNm9ezeXXnopu3btIi0tjWOOOYalS5dy1llnsXz5cj799FOAULf0vUpKShg6dChxcXG8/vrrXHPNNUyYMAGbzcb06dP5wx/+0K04zjrrLJ566ikefPBB3nnnndD2008/neXLl2MymZg4ceKhFzhGKPkWiQENvmbu/GwZM0adGJZ8t3qbQ4k3gAlIbm0Je24wEGxrGe+jyXd9fT0ZGRlGhyEiIiISNZ566qkOHzvttNOIZM7tIUOG8Oabbx5SHL/97W956aWXqKurY82aNZhMbc1D77//PgDp6encdttth/QesURjvkUkprndbqND6BW+pibWvPASvn40LkpERERi29ChQ3nnnXcYPXo0wWAw7GfMmDG88847DB482Ogwe41avkUkpvWXcUJ+j5e1ixZz5Bnfw5KcfMiv52tqYsPrSyg6d9JheT0RERGR9hx33HF8+eWXrF27luLiYgAKCwsZO3aswZH1PiXfIhLTqqurSUtLMzqMmHO4k3kRERGRzowdO7ZfJtz7Urdz6ZfikhIxmU2h+0GgKS6efUe/mMwm4pIin81Rep+vqYktb76trtg9SN3dRUQEwOVxM/uVZ3F5+sdwLzk8/vKXv3D66aczffr0Ax679NJLOf300/nLX/5iQGTGUMu3dOypp/B8/DHWAQOMjuSws6SkMPG5Z0JLdDXV1fH67bM484F7SE5PB/r+El19gd/jZdf7H+H/yYVqve0hfaaF/He/w7N7N9aTTzY6EolyTz0FH3/sYcAAq9GhSJT73e9g924PJ5/cP46VBm8Td742nxmnTsZutRkdjsSIp556ijVr1vDHP/7xgMeOO+44nnvuOerr6/nFL35hQHS9Ty3f0rFTT8WZlwfHHWd0JD3CkpKCNTsLa3YWqXkDGTvtB6TmDQxtU+It0occd1xbfXbqqUZHIlHu1FMhL8/ZV099chgdd1zbsaJqRaRjW7ZsAeCYY4454LHRo0eH7dMfqOVbOuXz+YwOoVdYkpMZd+EFRofRr7k8brz+tuOtwd/MExs/5epR3yY1oa3rf1KCRVfa5ZD0l/pMDp2OFYmUjhWRzrW0tC2BW1ZWdsBje7ft3ac/UPItnSooKDA6BOnE3rHre9f6DgKeuHisrS3sHdEeC2PXXR43Zzx0M4E9a062mqDCamHZ8jeJ2zMQ32wy8e7ND5HUGgwNF/DW1bX9rq3FvOe5hzJcwOXz8vDa97lp7HfD1lM/2P2ija+xscf+drFA9ZlESseKRErHikjnhg4dysaNG7nrrrs45ZRTKCwsBKC4uJi77747tE9/oeRbOvbBB9S+8w7WkSPhpJOMjkba0Z2x6/smXn6Pl83v/oejzvgeCdaksP2M4PX7Qok3QFwQ8prCWxMCwSCNdbV8cM2NYRcbkuLi+fimW8MuNkx87pmDKkuDr5k7P1vGjFEndppUR7pfNPE1NvL2/13eY3+7qPf559Ru2oTVaoVzzjE6GoliH3wA77xTy8iRVp36pFOffw6bNtVitVpVrYh04LzzzmPjxo2UlpYyZswYjjjiCAC+/vprWlpaMJlMnHfeeQZH2XuUfEvHrrySvPJyyMmBJUuMjqZPOhwtqJaUFNiTLAVMbWlUUkYG1qzM0D7tJV6euHh2/fvlmEq8Wpt9oTIAmIDk1vCuSsHAnpbxKC6HEVq9zf37b3fXXeRVVsLLL8POnUZHI1HsyiuhvDxPpz7p0l13QWVlnqoVkU78+te/ZsGCBZSVldHS0sJXX30FQHBPo0t+fj633HKLkSH2Kk24JtLLXB43u1217HbVUlJTwZ2fLaOkpiK0rSeW8Ogo8TLts08o8YpicYmWg1oiTstlaXk9ERER6X0ZGRl8/PHHTJ48GbPZTDAYJBgMYjabmTx5Mh999BGZmZldv1AfoZZvkV7U3thmh9XC9CfnHDC2WZOLHSjeZjuobvZNdXWsXbSYwceN67dLyWl5PRER6QnJliTMJjOBYKDDfcwmM8kxMkxLDr/8/Hxee+01amtrQzObjxgxgoyMDIMj631KvkV6UaRjm71+n5LvDhxsN/t+Nb65A5H87URERLojw5ZK1SMv0+TzArCrvobxd1/NqjueYGBa2/kl2ZJEhi3VyDAlCmRkZDB+/HijwzCUkm8R6XP68/jmWJ2JPVq4PG4efnsRN02cpgtgIiIRyrClHpBcD0zLZFBGjkERiVGuuOIKAH77298yfPjw0P3OmEwmnnrqqZ4OLSoo+RYR6cK+a5ADVDW52n431pEQaOtm1xPrkHe1NBgc2FU8Fmdi7yn7/t+yAgHigNZAAGdtJfBNS0ytuyGsxebO1+Zz7tgJarERERHppmeffRaTycTPfvYzhg8fHrrfFSXfIiJywDh96J2x+pF0nYe27vMnPjmXgCUBaP/CAPTMxYFotv//bYnbxQDA6aoh/5YLgbYxiFvmPMeI3/zfAWMVx999dei22WSm6pGXlYCLSL+z/8XJfX+DLk5KZILBYKePR5Kc9xVKvkVEOrH/OH3onbH6kXSdB/CYgkx64vedTuIH/W8iv/b+b/sLBANUu12dThK0d78mn1dfMEWkX6l1N5B9w/ndvjiZmpTMrCnTSU1K7rVYJXr85z//AeDoo48Ouy9tlHyLRKl9u8z2VjdniT1+s6nLSfzgwIsDCdYkxk77AQnW/t01XURE2tfk8x7UxUm71cbsqZf1cHQSrb773e+Gbjc3N4datQcNGsTw4cONCitqKPkWiUIN3iYmP3a7liSTHmNJTmbchRcYHUbM8jU0suGpZym68jIsqX1r0j4REZHDwWKxcPrppxMMBvnHP/6h5Bsl39KZr77C/+67JPSjhe+jRXOLX0uSSUzxNTWx4fUlFJ07CUty9HU1/MEZY0jxt/DhwPTD8np+t5u1j83lyB9PU/Ldx3z1Fbz7rp/MzASjQ5Eot3gx1NT4OeMMHSsi7TGZTAwaNIgdO3aQlZVldDhRwWx0ABLdvv76a6ND6JcS4xMw7zP5RKsJypMttO4zH4XZZCIpwWJAdCIH8nu8rF20GL/Ha3Qo3WJNsGA2dX4qNJvMJFuSaK6vx+2swO2swFPZNmO6p7IytK25vr43QpZeoHOfRKovHyvJlqSI60eRjsyYMYNgMMg///lPo0OJCmr5lk6Zzbo+Y4TUpGTevfmh0JjvXU0uxi1+nLcu/hUDk+2AxnyLHA7pySlUPfJy2Gy+4+++mlV3PBG21FhyS4B/HX8SwUD4+Mc3pk4L3TaZzVy0egWJaWm9VwDpETr3SaT68rGSYUuNqH7UZJTSmUGDBnHEEUfw3HPPUVJSwrnnnktubu4BM5xfeumlBkXYu5R8S6cGFxQYHUK/ZbfaQsm1f8/JPTslnQEp+mIv0aGrdcj3X4M8WmXYUg/48jgwLZNBGTmh+25nxQGJ9/6CgQAtHq+S7z6goGCw0SFIjOjrx0ok9aNIZ6688spQov3xxx/z8ccfH7CPyWRS8i3CnDk0ffQRScOHwy9+YXQ0ItJLIkmqgS7XITeZTUx87pmoSMAvL95Fhs/Pdyrq+d0JRxgdjkSxOXPgo4+aGD48Sac+6dTTT8PWrU2sWpXE3XcbHY1I9Opqne/+RMm3dOyZZ8gsL4cNG5R8i/SyuKRETGZTWHLriYvH2tpCWEetLsbjdZevsTGipPrUxx7qch3yYCDYlsRHQfJ9Xlk1A7x+dlY2KPmWTj3zDJSXZ+rUJ1167TWorMzkq6/o1eTb5XHz8NuLuGniNA0/k6g3a9Yso0OIKkq+RfoQrd3cJpLE1WQ2hVpwo5ElJYWJzz0TaoFuqqvj9dtnceYD95Ccnh7ar7rFw0N/v+uwvW+rtzmypNp34FriIiLSM2rdDWFjr+98bT7njp3Qq2OvU5OSmTVlOqlJ0beihRxo3rx5zJs3j23btgEwevRofv/73zNp0iQAvF4vN998MwsXLqS5uZmzzz6bv/zlL+Tm5oZeo7S0lGuuuYb//Oc/pKSkMH36dO69917i4yNPIZV8h1PyLdKLkhIsmE2msPW7K6wWcj2+sPW7D3YW8/62dnOCNYmB3z3lgIsNkSSusTAe2ZKSEmo1DuwZL5WUkYE165vl/+wed5fHFER+XEV84cKimfZFRHpDrbuB7BvOJxAMn3di/N1Xh26bTWaqHnm5RxNwu9XG7KmX9djry+GVn5/Pfffdx5FHHkkwGGT+/PlMnTqVL774gtGjR3PjjTfyxhtvsGjRItLS0pg5cyY//OEPQ2OyW1tbmTx5Mg6HgxUrVrBr1y4uvfRSEhISmDNnTkQxfP7553z44Yf4fD6OPvpozj777AMmWutvlHyL9CK71XZQs5inWhKZdcJZpFqit6XWCJbkZIadc2a760pHkrjGko56NURyTEHks+NHeuFi7+MiItKzmnzeAxLv/QWCAZp8Xs08LiFTpkwJu3/PPfcwb948PvnkE/Lz83nqqadYsGABp59+OgDPPPMMo0aN4pNPPuHEE0/k7bffZsOGDbzzzjvk5uYybtw47rrrLm699VZmz56NpYuL8D/72c945plnwraNHz+eJUuWkJGRcXgLG0P67voIIlHKbrUxwJ7BAHsG2SnpwJ5ZzPdsay9BsluSmD3+bOxaS/MADofD6BB6xd5eDe1daOjqmOrouOrwvVJSsGZnYc3OImnPCTIpIyO0Ldp7DBwKdasUEZFo5nK5wn6am7u+GN7a2srChQtxu91MmDCB1atX4/f7OfPMM0P7jBw5koKCAlauXAnAypUrOfroo8O6oZ999tm4XC7Wr1/f6fs9/fTTPP300wSDwbCfVatWceONNx5kyfuGbrV8r169mpyctqUFKioqyMvLw+fzUVVVxeDBg2lsbKS2tpahQ4dSU1ODy+Vi+PDhOJ1O3G43hYWFlJaW4vV6GTVqFFu2bMHv9zNmzBg2bNhAIBBg7NixrF27FqDd22azmaKiItatW0dCQgIjRoxg48aNJCUlUVBQQHFxMTabDYfDwdatW7Hb7WRmZrJt2zYyMjJISUmhrKyM7OxsLBYL5eXloYNKZQov01F+PxbA39JC8fr1DB8+nJKSEgKBAIWFhRQXFwO0e9tsNjNs2DC2bt1KfHw8gwcPpqSkBEtiIg6Hg9Lt27FarWRlZbFjxw5sNhtpaWmUl5djt9uxWq1UVFSQnp5OQkIClZWVZGZlAVBTXU1OTg5+v5+6ujpyc3PxeDy4XC7y8vKor6/H7XaTn59PdXU1Ho+HgiFDcDqd+JqbGTZsGGVlZbS0tBhepubktquGm4s3k5A/tMfK1OJyRfQZ93o9fL1+fa//n7aXlUYU3+biYjLGHhf2v/ni88/Jysrq9P+0d393k5ttzl0dlqkpwRz6f5A7iISEBDaXlkQUG8COHTuoDJYbeuxt3roZgLr6Ouq27zjk/9PuHTsAaGhooKK+LlSmHXvGkHWl+KtiitJO6PU6IsmeEtYdvz1mk5nSku2Ub9kWVpf/6owfsWXzV2F1eXNVVUTl9Xq9bFi1Kqrq8r54furJMvn9VsBCIBBg/fqNER17WXt61FRX13T7/DRkSAFOp5PmZt9hryMSEy04HA62by/t9udJZeq6TH7/EUACfr+PVavW9tjnac36tRHVP7ucTnx1jVH1eeqLdYQRZSorK2PMmDEADBw4kKamptD/fdasWcyePbvdY+LLL79kwoQJeL1eUlJSWLx4MUVFRaxZswaLxUL6PnPIAOTm5uJ0OgFwOp1hiffex/c+1pmnn346dHvYsGHY7Xb+97//EQwG+de//sVf//pXEhP7Z29OU1Bzv0tHBg2C8nLIyYElS4yOpk/a2VhP/v+7ix2X/I5BPbh+t6eqmneu+HmX+5359F+xZmf1WBwd2e2qZdKjt3W535Jf3scAe3hXpa+//pojjuh89mp3dQ0vXn09P3riMWyddDtv7//h8rg546Gbw5K4jsbqv3vzQ4bPPHu4j6mO/nbRcky5fF4eXvs+N4397gE9Q1wed6g7fvqPLsJSU4MvdwCVG9cB3ZugyO2s4MWTTutyvx+tWI7NkdvlfhK9dOqTSE2aBJWVkJcHO3f23PvsrK0k/5YLu9xvxwMvaP3tfsC1X4NKYmJih4msz+ejtLSU+vp6XnzxRZ588knef/991qxZw+WXX35Aq/m3vvUtvve973H//fdz1VVXsX37dpYuXRp6vKmpCZvNxptvvhmauK096enpNDQ08LOf/Yy//vWvAPy///f/mD59OiaTibVr14YuJvQ3GvMtIjEtK6tnLxbsP6YaIh+r3xdE+wz6Db5m7vxsGTNGnXhA8m232kL/k1Zz27j/OJNZX05FRCRm2e32rnfaw2KxMGLECACOP/54Vq1axaOPPspFF12Ez+ejrq4urPW7oqIiNJzP4XDw3//+N+z1KioqQo91xuVyYTKZuOiii0LbLrroIqZPnw609abrrzTmW0Ri2o493aJ70r5jqrszVt8Ih3tyvs7GmouIiEjsCAQCNDc3c/zxx5OQkMC7774bemzz5s2UlpYyYcIEACZMmMCXX37J7t27Q/ssW7YMu91OUVFRRO+XlPTNRfF9J2jrzx2v1fItHTvlFDzr1mEdNMjoSEQ6ZLMdWtK7b9fkqqa2rlxVjXUkBNpmlo21Fu29k/NJuMDYsXxV8hXDj/0WcUYHI1HtlFNg3ToPgwZZjQ5Foty4cbBzp4cxY3SsSPS5/fbbmTRpEgUFBTQ0NLBgwQKWL1/O0qVLSUtL48orr+Smm24iMzMTu93Oddddx4QJEzjxxBMBmDhxIkVFRVxyySX88Y9/xOl0cscdd3DttddGPF57zpw5DBgwoMvtJpOJp5566vAUPMop+ZaOPfMMza+9hjU/3+hIRDqUlnbw45r3H8/dagKH1cL0J+dE3VhuOTQJd/4Bx44dJOy39IrI/p55Bl57rZn8fCVU0rlZs2DHjmamTNGxItFn9+7dXHrppezatYu0tDSOOeYYli5dyllnnQXAn/70J8xmMxdccAHNzc2cffbZ/OUvfwk9Py4ujtdff51rrrmGCRMmYLPZmD59On/4wx8ijmHJfhNn7F3je//tgJJvEYAKp5N0Jd8SxcrLy7tcL7Kjcctevy9sIrW4IOQ1+cL2CQSDeP0+Jd99QIXTSbrRQUjU8zc2UvfyI+Rd+StI6rvL6snh4XRWgGoWiUJdJbNJSUnMnTuXuXPndrjPkCFDePPNNw/q/bvTtXxvUt4fKPmWTqX04fV8pW+IZOKRveOWpX/rrfqsub6eFo+3w8fjrUkkHkKPDelZLW43SZ/+i8BPr4EMnQOlc/qeJHKgWbNmGR1C1FLyLZ2yWtWVSqKbjlGJVG8cKz5XAy+dcjrBPXMGtMdkNnPR6hVKwGNco8/N82sXcfHYaaRYOu4Z09rUSNXrz5J97mXEJStR62t0DhI5kJLvjmm2c+nYpEnYbr4Zrr/e6EhEOrR32QuRTl1/fVt91sm6pIdDa7O308QbIBgIdNoyLsY6/+IMfrPjNW78befDWZp8Tfz9s/k0+Zo63S/gcVO5aC4Bj/twhilR4Prr4eabbT1drYhIH6KWb+nYli0kOp3Q2mp0JCId2nd9SpEOlZWRWFkJZl1zls5tLYljl38EvnKd+6RzZWVQWZmoakVEIqbkW0RiWkJCwkE/NynBgtlkCpt0bX9mk4mkBEvYtsO9lraIxIbwpQnr23431kOg7evU3qUJfY0NtHrb9mupqwXAW1tLS7Btv7gkC5aU1N4OX0REDKbkW0RiWmVlZbtrSEbCbrXx7s0Phb5Mt6e9db61lrZI/7N3acLQDL6mVrBmcumT90GwbfV4k8nEWz//AytnXAt7hh+YaCUtLpvtN91GcO8q82YzE597Wgm4iEg/o+RbRGJaZlbWIT3fbrVpGbEYE9766Gr73VhHwp5kp70LJiKHyuv3hS+dE4yDpuywfYLBIB53YyjxBggSR13rfhcIA4G2lnHNvyYi0q8o+RYRkZixt/Vx71CBVhM4rBamPzmHuD15kdlk4t2bHzqsCXi8NQmT2dzlLOZxSRqKEK1cHjcPv72ImyZO08UZERExhJJvEYlpNdXVDHQ4jA5DeonX7wsbox8XhLym8GEDgWAQr993WBOsxLQ0Llq9IjRLud/tpvifL1D4kwtJsLW9T7w1SbOYR7EGbxN3vjafGadOVvItUamjC0TJliTMJjOBYMcX/8wmM8mWpN4IU0QOgZJvETHc/hOftZqgwmoh1+MLa83cf+IzgJycnN4MVfqxxLS0sLW5v3XHbQfso+Q7utS6G2jytf1PdtXXhP2GtqQmwxbZuOukBAsmk2m/Md+14MkIG/OdGH/wk0BK/7P/MXrna/M5d+wEBqZlhvZJtiRR9cjLYfuNv/tqVt3xRGi/7hzLImIcJd8iYrj9Jz7b1eRi3OLHeeviXzEw2Q50PI7X7/f3aqwiEhtq3Q1k33D+Aa2F4+++OnTbbDJT9cjLJLd8s/Z6sDUTiINAAE9VHdA2O7k9JTWsnqpqqubSxTP4x8X3k53cNvdEUoKFBLcuwEhkIjlG4ZvjdFBG+MXmgWmZB2wTkeim5FtEosK+E5/59yyamp2SzoCUtM6eRl1dHYMGDerx+EQktjT5vJ120wUIBAPUV1Xy2hlTQuP5vTXLgVya6128e8VVbTvumZ3cnpL6zUVAcwsA2SlpDEjJCL2mR8m3RCiSYxTajtMmn1ct2yJ9gJJv6djtt9P0ySck5+UZHYlIh3Jzc40OQWLBZZfRVF5O8oknGh2JRJlWrzdsIr3JaX9jh6+QZLPrm500O7m047LLoLy8iRNPTO7V901NSmbWlOmkJvXu+4rIoVPyLR274gpqrVaSR440OhKRDnk8HqNDkFgwdSq1mzaR/JOfGB2JRLlTU//NZu/xJJncRofSK1qbGql6/Vmyz72MuGRdXeiOqVNh06ZafvKT3k2C7VYbs6de1qvvKSKHh9noACS6NTY2Gh2CSKdcLlfXO4mg+kzaF5fUtozcN4LkJpRipvWbTWYzcUkHTvjYFwQ8bioXzSXg6R8XGw431Ssi0h1q+ZZO5WoJJzFAqiWRWSecRaql6zWT8zQsQiKk+kzak2BPDVtGrqa0kvd+PI2xdz+GzdE2mVVckgVLisbbyoEcDg19EpHIqeVbOrZrF03bt0NVldGRSD9jtyQxe/zZ2CNYs7S+vr4XIpJosXdZur1aTVCebKH1m03tL0tXVdVWn+3a1UuRSixJTEvD5sjF5sjFFcylpiUXN1lYs9t+lHh3zuVxs9tVy25XLduqd/LwR/PYVr0ztM3VR1vVq6pg+/YmVSsiEjG1fEvHTj2VvPJyyMmBJUuMjkakXW533/xSF+3ikhIxmU0EA21rHgcBT1w81tYW9ubBJrOJuKSuey90x0EvSzdjBnmVlfDoo7Bz52GNSfqWs87PZJdzOdk3t/LWUqOjiX4uj5szHrr5gPXPFyxfHbb++bs3P9TucpGxbMYMqKzMU7UiIhFT8i0iHXL5vDy89n1uGvvdiFqhjZCfn290CP2SJSWFic89Q6u3GYCmujpev30WZz5wD8np6UBbgm5JOfwTOB3ssnS9Id7aNn5439mz92cym4m3RufnSfoHX2ND2+ztQEtdLQDe2lpagm1fC7vTzd7r932TeENbwt2UHbZPMBjE6/f1ueRbRKS7lHyLSIcafM3c+dkyZow6MWqT7+rqatLSjE+6+iNLSgrsSa4De7qCJ2VkYM3KNDIsQyWmpYWNH/ZUVvLG1GlMfmUR1py28cPx1iQSo+SY9TU0suGpZym68jIsqZrp2ki9Neu4r7GBt//vCthzgchEK2lx2Wy/6TaCtLVU713XXN3tRUQOL435FpGYpqXGJNrsO354b8JtzckJbYuWxBvA73az9rG5+DV8I8S050KSaZ+5BXpDb8063ur1hRJvgCBx1LUO+Cbxhm/WNe/JOJoaqXjhz7Q2abZwEek/1PItIjGtYMgQo0MQA3VnZnyRiJjM4b/lsAnv7l5J5aK5JB93JvHpmlVeRPoHJd8iBlLicOicTiepI0YYHUa/l2BNYuy0H5DQy2OZ986MLxKLDufY62jX4nbz9jU3qru7iPRrSr5FDKTE4dD5mpuNDkEAS3Iy4y68wOgwRGKG393Euz+7OmaS0Uafm+fXLuLisdNIsXR/4rRAc/vd3cN32tPdXdMPiEgfpT5VIhJm3/VaqxrrAKhqrIva9VqHDRtmdAgiIt0W8DdHxdjrSDX5mvj7Z/Np8jUZHYqIRODee+9l/PjxpKamMmDAAM4//3w2b94cto/T6eSSSy7B4XBgs9k47rjjeOmll8L2qamp4eKLL8Zut5Oens6VV15JY6PmajhYavkWkRBXs4dzn/gtgT3LxrSawGG1MP3JOcTtWUnGHGXrtZaVlXHUUUcZHYaIiIhI1Hj//fe59tprGT9+PC0tLfzmN79h4sSJbNiwAZut7TvcpZdeSl1dHa+++irZ2dksWLCACy+8kM8++4xjjz0WgIsvvphdu3axbNky/H4/l19+OVdddRULFiwwsngxSy3fIhLS3OIPJd4AcUHIa/KFEm+AwJ71WqNFS0uL0SGISD+UbElmxgnTSbYkGx1Kn6ZZ0UUOzltvvcVll13G6NGjGTt2LM8++yylpaWsXr06tM+KFSu47rrr+Na3vsURRxzBHXfcQXp6emifjRs38tZbb/Hkk0/y7W9/m1NOOYXHH3+chQsXUl5eblTRYppavqVjb7xB84cfkpidbXQkIh0aPny40SFILHj0UZqrqkj8zneMjkSi3BtvwIcfNpOd3flEmCkWGz8ff1nvBNXPxMqs6I8+ClVVzXznOwceK7XuBpp8XgAavE387YPXuerUc0lN+uZiTV1TdA3jkr6tvr4egMzMzNC2k046iX/9619MnjyZ9PR0XnjhBbxeL6eddhoAK1euJD09nRNOOCH0nDPPPBOz2cynn37KD37wg14tQ1+g5Fs6VlhI6YcfcmRBgdGRiHSopKSEUaNGGR2GRLuCAkqrqjiysNDoSCTKFRbChx+WUlBwpNGh9EuxNBFdQQFUVZVSWBh+rNS6G8i+4XwCwUDY9j8tezHsvoneXUte+gaXyxV2PzExkcTEzi8WBgIBbrjhBk4++WTGjBkT2v7CCy9w0UUXkZWVRXx8PMnJySxevJgRe1aRcTqdDBgQPjFifHw8mZmZOJ3Ow1Si/qVbyffq1avJyWm76lhRUUFeXh4+n4+qqioGDx5MY2MjtbW1DB06lJqaGlwuF8OHD8fpdOJ2uyksLKS0tBSv18uoUaPYsmULfr+fMWPGsGHDBgKBAGPHjmXt2rUA7d42m80UFRWxbt06EhISGDFiBBs3biQpKYmCggKKi4ux2Ww4HA62bt2K3W4nMzOTbdu2kZGRQUpKCmVlZWRnZ2OxWCgvLyc3N1dlaqdMvro6knw+iouL8cfFMXz4cEpKSggEAhQWFlJcXAzQ7m2z2cywYcPYunUr8fHxDB48mJKSEiyJiTgcDkq3b8dqtZKVlcWOHTuw2WykpaVRXl6O3W7HarVSUVFBeno6CQkJVFZWkpmVBUBNdTU5OTn4/X7q6urIzc3F4/HgcrnIy8ujvr4et9tNfn4+1dXVeDweCoYMwel04mtuZtiwYZSVldHS0tJvytSyX0XdkWavN6L9NhcX05ybFxX/p8rKyrDtsfx/6ovHXrSUyVtXR1V1NemVldR4vb1Wl/9v7RoAGhpcbCgrjbrz05EOBwBr167hhMzvxcz5KZL/0253fUT1mdvdxKotq0Jl+t//tlBfH6C+vp6tWyM79rKy2lqSqqtryLAlg9m8X/JYTX1rVljyWL57d0TxFX9VTFHaCQf1eUpMtOBwONi+vTT0edr2VXFE71tZuRtLi4/q6hpycnJwuioAqKmtobnWG6ojdlc6MZkgNGLJ1ArWWvBkQLCtvCYT7Ni+PaL39XncEc2KvvHLdaTm5narjtj3/9Tdem/IkAKcTifNzb5Qved2t+L3wxdffI7F0hp27O2feLcnSLDLffYq2baNuOZWfYftp2UqKysLJc0DBw6kqembiQ9nzZrF7NmzOz1+rr32WtatW8dHH30Utv13v/sddXV1vPPOO2RnZ/Pyyy9z4YUX8uGHH3L00UdHfHxK5EzBYDDyT770L01N+N99l4TMTEjq3bV75fDyVFXzzhU/73K/sY8/wA/+cV+X+y355X0MsGccjtAOmd/vJyEhwegwJNp5vfhrakg44wxI7r0xur6GRjY89SxFV16GJTX61k9yOyt48aTT+NGK5dgcuUaHc1jtrK0k/5YLu9xvxwMvMCgjJ3S/qQnefddPZmbCQZ/69u82vf32HzDk3sVh3aYB3v6/K7pM0g93C6+nqpp3r7iqy/3OePpvWLOzQvd3N1by/f93IW9e8gIDUnLC9nV53KG5QKqaqrl08Qz+8YO/k53c9vykBAtJrYGIynvqYw/xwcwbux2fEbxeqKnxc8YZCWHVSqTHXnfsf5xK/9Xdlu+ZM2fyyiuv8MEHH4StELN161ZGjBjBunXrGD16dGj7mWeeyYgRI3jiiSd4+umnufnmm6mtrQ093tLSQlJSEosWLVK384OgbufSsX/9i+qlS3EcdRScd57R0Yi0q7i4OOykIdKut9+mevNmHFVVcPnlvfa2ltQUxt0ws9feryvN9fW0eL7p4eKprAz7DRBvTSIxLS3sedF+EeFw+te/YOnSao46ynHQpz5LSmporWq/qW1SyKSMDBKywpPFic89fUCSPvaBv0fd2Oau2K22b1bAMLeVNzsljQEp4RdpIylvtCytFom334bNm6upqnL0ZrUi/Zzdbo9ov2AwyHXXXcfixYtZvnz5AUuz7m09N5vD59+Oi4sjsOci2YQJE6irq2P16tUcf/zxALz33nsEAgG+/e1vH2pR+iUl39KxO+7AUV4OOTlKvkUkts2bh6OyEj78sFeT72jSXF/Pv44/iWDgwO6wb0ydFrptMpu5aPWKsATc73az9rG5HPnjaX0++b7jDigvd/TKqS/SJL2viKS8Hm+1EaEdlHnzoLLS0Z+rFYli1157LQsWLOCVV14hNTU1NEY7LS0Nq9XKyJEjGTFiBD//+c958MEHycrK4uWXX2bZsmW8/vrrAIwaNYpzzjmHGTNm8MQTT+D3+5k5cyY//vGPycvLM7J4MUvJt4jEtEJNoCUSkRaPt93Ee3/BQICmisqDaiGXA5mtNnKmXYt5b8twH6cl2ESiw7x58wBCM5fv9cwzz3DZZZeRkJDAm2++yW233caUKVNobGxkxIgRzJ8/n+9///uh/Z9//nlmzpzJGWecgdls5oILLuCxxx7rzaL0KUq+RSQkMT4Bs8kUWuu71QQVVgu5nm/W+jabTCQlWAyMMpy6nYscfq9+f2rYpFd7ddVCLgeKS04h98LoGXrQ07QEW/fse87teB8zyRbNvSPdE8m0XkceeSQvvfRSp/tkZmayYMGCwxVWv6fkW6QfiEtKxGQ2EQx0XBGbzCYy0tJ59+aHQhPn7GpyMW7x47x18a8YmNw2xigpwfLN2D4R6ZsibCFv8XiVfIscgv/Nfor05La++Lvqaxh/99WsuuMJBqZ9sxZzsiWJDFv0j/0Xka4p+RbpBywpKUx87hlavc0d7hOXlIglJQULhJJr/55JOLJT0hmQEp1fsNXtXEREYlV6csoBs5gPTMvUzOYifZSSb5F+wpKSAil9b6IkdTsXkb4gGseGhy8h1rZuelVjPQTavj6qJ9ThlZqUzKwp00lN0nh5kb5KybeIxLT9l8gQEYlF0TY23NXcxLlP/PabcaOmVrBmcumT90GwbV1uk8nEuzc/pAT8MLFbbcyeepnRYYhID9K3VhGJafuvWykiIoeuuaUlfMKmYBw0ZYcSb2ib0Glvy7iIiHRNybeIxLStW7caHYJITIi3JmGKpKeIydTzwYiIiPRD6nYuHcvNpaWpifjMzK73FTFIfLyqMYlAZiYtfj/xublGR2KYxLQ0Llq94oD1u9+YOo3JryzCmtM2wZOvwcWrZ5/XY3G4PG4efnsRN02cFpXdlXNzoamphcxM1S3SucxM8PtbyM3VsSIikVFtIR376CP8S5cSP2CA0ZGIdGjw4MFGhyCx4Kmn8O/eTfzZZxsdiaES09LaXRrMmpODzdE7FyYavE3c+dp8Zpw6OSqT748+gqVL/QwYoK9I0rmnnoLdu/2cfbaOFRGJjLqdS6dKS0uNDkGkUyUlJUaHIDFC9Vn/kmxJwmzq/GuO2WQm2ZJ0wHYdKxIpHSsi0h26VCedslgsRocg0ilLYqLRIUiMUH3Wv2TYUql65GWafG3d7Bu8Tfztg9e56tRzQ0s5JVuSyLClHvBcHSsSKR0rItIdSr6lUznqci5RzuFwGB2CxAjVZ8apdTeEkuBd9TVhv/fqKBE+FBm21LDXfPiiayN63oABOYc1Dum7dKyISHco+ZaOXXcdwdWrYcgQ+P3vjY5GpF2l27czevRoo8OQaPfHPxLcvh3efLNtoKb0mlp3A9k3nE8gGAjbPv7uq8Pum01mqh55+bAn4N113XWwenVQp74eZrbayJl2LeYoHPcfqT/+EbZvD6paEZGIKfmWjr31Fqnl5VBebnQkIh2yWq1GhyCxYOVKUisrobLS6Egkyr31FpSXp+rU18PiklPIvXCm0WEckpUrobIy9YBqZe98A/tfcNpfR3MOiEjfpeRbRGJaVlaW0SGISCf2H3u9q76G8Xdfzao7nmBg2jdLWfZEt3MRI+iYF5GOKPkWkZi2Y8cO0tpZOklEosf+Y68BBqZlMihD42UldgWDAcAc+r0vHfMi0h4l3yIS02y22B0vKCLS2+KSLGA2Q6CTLtFmM+bEhN4LKoa4PG68fh8ALYFUwExLoJWdtdWhfdSiLSIdUfItIjFNrd4ixqn1NFJX+02LX3eW8xJjWFJSmfjc07R6fR3uE5dkoS7Q0otRxQaXx80ZD91MMBhs29B0H5BBZUMd+bdcGNpv/8kDU5OSmTVleugzISL9l5JvEYlp5eXlZGRkGB2GSExKsNkYe/21JBxEDxJ3vIkhc2YQ2JuI7ONPy14M3Y6WWczlG5aUVEjpYidXba/EEq1amxqpev1Zss+9jLjktj+W1+/7JvHuRCAYoMnnDR3zdquN2VMv68lwRSRGmLveRUQketntdqNDEIlZltQUxt0wE0tqV5nYgXxmU7uJ9/72JiIisSTgcVO5aC4Bj9voUESkD1HyLSIxTUuNiYiIiEgsUPItIjGtoqLC6BBERPqcpAQLJpPpmw2mVkiuavu9d5PJRFKC5bC+b2hCuL3vQSvpcbsx8c37Yja37SciEmM05ls6Nm0aTZ9/TnJ+vtGRiHQoPT3d6BAkFpx5Jk07dpB83HFGRyJRbto0+PzzJvLz+/fkWHarjXdvfig0s3dVUzWXLp7BPy6+n+zkLKAtQbdbD++KE/tPCBfwuKl7dyHpZ/wY8573ikuytI1bN1reami2Q3qp0ZGISIxQ8i0dmzMH97//TfKwYUZHIgZJtSQy64SzSLUkGh1KhxIStByORODaa3GXlJD8wx8aHYlEuTlz4N//djNsWP9OvqEtAQ8l1+a22c+zU9IYkNKzk1yGTwiXhe2yX/fo+x20US+DPxkG/s/oSEQkRqjbuXSqprq6652kz7Jbkpg9/mzsliSjQ+lQZWWl0SFIjFB9JpGqrq4xOgQREemDlHxLp7SEk0S7zKwso0OQGKH6TCKlY0VERHqCkm8REREREZE+5N5772X8+PGkpqYyYMAAzj//fDZv3nzAfitXruT000/HZrNht9s59dRT8Xg8ocdramq4+OKLsdvtpKenc+WVV9LY2NibRelTlHxLx449lqyrroKf/tToSEQ6pK7EEpGf/rStPjv2WKMjkSh37LFw1VVZOvVJ15bfAe/+ARb/3ehIRA7w/vvvc+211/LJJ5+wbNky/H4/EydOxO3+Zu36lStXcs455zBx4kT++9//smrVKmbOnIl5nxUHLr74YtavX8+yZct4/fXX+eCDD7jqqquMKFKfoAnXpGONjcQ1N8M+V79Eok1OTo7RIUgs8Hja6jNdrZcuNDZCc3OcTn3StdZEaE2CluidF0X6r7feeivs/rPPPsuAAQNYvXo1p556KgA33ngj119/Pbfddltov6OOOip0e+PGjbz11lusWrWKE044AYDHH3+c73//+zz44IPk5eX1Qkn6FrV8i0hM8/v9RocgIt2QmpTMrCnTSU3SbOKxJNmSzIwTppNs6Zv/N19jA56q6tCPt7YWAG9tbWibr8ndxauI9DyXyxX209zcHNHz6uvrAcjMzARg9+7dfPrppwwYMICTTjqJ3Nxcvvvd7/LRRx+FnrNy5UrS09NDiTfAmWeeidls5tNPPz2Mpeo/utXyvXr16lArU0VFBXl5efh8Pqqqqhg8eDCNjY3U1tYydOhQampqcLlcDB8+HKfTidvtprCwkNLSUrxeL6NGjWLLli34/X7GjBnDhg0bCAQCjB07lrVr1wK0e9tsNlNUVMS6detISEhgxIgRbNy4kaSkJAoKCiguLsZms+FwONi6dSt2u53MzEy2bdtGRkYGKSkplJWVkZ2djcVioby8nNzcXJWpnTId5fdjAfwtLRSvX8/w4cMpKSkhEAhQWFhIcXExQLu3zWYzw4YNY+vWrcTHxzN48GBKSkqwJCbicDgo3b4dq9VKVlYWO3bswGazkZaWRnl5OXa7HavVSkVFBenp6SQkJFBZWRmaWKumupqcnBz8fj91dXXk5ubi8XhwuVzk5eVRX1+P2+0mPz+f6upqPB4PBUOG4HQ68TU3M2zYMMrKymhpaVGZ+kCZtm7dSl1dXZ8qU1/8PxldpvTWVuKB1kCALZs396u6vLtl8tcc/pm+S0vLoMkXKtMVx57O5nUbovKc6/dbAQuBQID16zdGdOxlZbV9ma2urun252nIkAKcTifNzb7D/nlKTLTgcDjYvr2025+n9sp0SvJ4vC4PtZ6aPlOmuro6slJS+eyXN0MgEDpmTbSSFpfN9ptuI0gcAC5LHIyNbDI+n9/PqlWrunXsxUodoTL1fpnKysoYM2YMAAMHDqSpqSl0rM2aNYvZs2d3ejwGAgFuuOEGTj755NDrfP311wDMnj2bBx98kHHjxvGPf/yDM844g3Xr1nHkkUfidDoZMGBA2GvFx8eTmZmJ0+mM6LMg4UzBYDBodBASpQYNgvJyyMmBJUuMjkakXVVVVWRnZxsdhkS7SZOgshLy8mDnTqOjiWpuZwUvnnRal/vVWszceMqALvcD2PHACwzKiI0hIjr19T+eqmrevaLrMayuBDMPj8v8ZsPS+8CbAcmV8JMLw/aNpWNeYovL5Qq7n5iYSGJiYqfPueaaa1iyZAkfffQR+fn5AKxYsYKTTz6Z22+/nTlz5oT2PeaYY5g8eTL33nsvc+bMYf78+QdM1DZgwADuvPNOrrnmmsNUqv5DY75FJKZ5NDBTRERE+gm73d6t/WfOnBmaKG1v4g1tLegARUVFYfuPGjWK0tJSABwOB7t37w57vKWlhZqaGhwOx8GE3+9pzLeIxLT9rwCLiIj0hIRAEJOp6/3MJjPJFk3CJsYKBoPMnDmTxYsX89577zFs2LCwx4cOHUpeXt4BrdrFxcUMGTIEgAkTJlBXV8fq1atDj7/33nsEAgG+/e1v93wh+iC1fItITNNMmyIi0husrUFev/wOTKkpAPz0w1TqvJCTms4XD7wQ2i/ZkkSGLdWoMEUAuPbaa1mwYAGvvPIKqampoTHaaWlpWK1WTCYTt9xyC7NmzWLs2LGMGzeO+fPns2nTJl588UWgrRX8nHPOYcaMGTzxxBP4/X5mzpzJj3/8Y33/OkhKvkUkptXX15OREdkEOCIiIofCnpiM1d52zokztwJtLd0a3y3RZt68eQCcdtppYdufeeYZLrvsMgBuuOEGvF4vN954IzU1NYwdO5Zly5YxfPjw0P7PP/88M2fO5IwzzsBsNnPBBRfw2GOP9VYx+hwl3yIS09xuLf0iIiIisq9I59S+7bbbwtb53l9mZiYLFiw4XGH1e0q+pWOPPUbTRx+RvGdCBpFotO/kISId+tWvaNq1i+RTTjE6Eolyjz0GH33UxMCBfXM9azl8fn5dI3Pe/xN/uPRGIM3ocEQkBmjCNenYpElUjhwJJ59sdCQiHaqurjY6BIkFJ5/cVp9NmmR0JBLlJk2CkSMrderrR+KSLGAO/0psopX0uN2YaP1mo9nctu8e40/0wbD3Of0sX2+FKiIxTi3f0imv12t0CCKd0lJjEinVZxIpHSv9iyUllYnPPU2r95skuqWuku23/4CxD/yd+PS28dxxSRYsKZpITUQOnpJv6dQgdemVKFewZzkMka6oPotMvDUJk9lMMBDofEdz3+08l58/yOgQpJdZUlIh5Zv7flMLAEkZGSRkZRkUlYj0NUq+pWNffIHrk09IGTkSxo0zOhqRdjmdTlJHjDA6DIl2mzbh2rSJFIdDQ2m6kJiWxkWrV9Di+ab111NZyRtTpzH5lUVYc9paASt8bm78w5VGhdljvvgCPvnExciRKTr1Sae2fhUPFUWs+188I7TqkohEQMm3dOzCC8krL4ecHFiyxOhoRNrla242OgSJBbffTl5lJSxYADt3Gh1N1EtMSyMx7ZsJpBJsNsZefy32oUOx7FnjOLG20qjwetSFF0J5eZ5OfdKle2fboWouV3/Wyvm7jI5GRGKBkm8RiWnDhg0zOgSRPs+SmsK4G2YaHYaIiEhM67sDtkSkXygrKzM6BBER6WPMVhs5067FbLV1uI8JU9u+JlNvhSUiMU4t3yIS01paWowOQURE+pi45BRyL+y8t4fJZA77LSLSFdUWIhLThg8fbnQIIiIiIiJdUvItIjGtpKTE6BBERERERLqk5FtEYlqgq7WIRURERESigJJvEYlphYWFRocgIiIiItIlJd8iEtOKi4uNDkFEREREpEtKvkVERERERER6mJYak459/jn+5ctJyMw0OhKRDqnbuUTk+efx19SQcNppRkciUe7zz2H5cj+ZmQlGhyJR7vnnoabGz2mn6VgRkcio5Vs6lprK104nJCcbHYlIh9TtXCKSnNxWn6WmGh2JRLnUVHA6v9apT7qUnNx2rKhaEZFIKfkWERERERER6WFKvqVTRxxxhNEhiHRK3c4lUqrPJFI6ViRSOlZEpDuUfEvHHnuM+rlzYeFCoyMR6ZC6nUtEFi5sq88ee8zoSCTKPfYYzJ1br1OfdGnhwrZjRdWKiETKFAwGg0YHIVFq0CAoL4ecHFiyxOhoRNq1ceNGRo0aZXQYEu0mTYLKSsjLg507jY6mT9hZW0n+LRdGtO+OB15gUEZOD0d0eOjUJ5FStSIi3aWWbxGJacOGDTM6BBERERGRLin5FpGYtnXrVqNDEBERERHpkpJvEYlp8fHxRocgIiIiItIlJd8iEtMGDx5sdAgiIiIiIl1S8i0iMa2kpMToEERERESiyr333sv48eNJTU1lwIABnH/++WzevLndfYPBIJMmTcJkMvHyyy+HPVZaWsrkyZNJTk5mwIAB3HLLLbS0tPRCCfomJd8iEtMsiYlGhyAiIiISVd5//32uvfZaPvnkE5YtW4bf72fixIm43e4D9n3kkUcwmUwHbG9tbWXy5Mn4fD5WrFjB/PnzefbZZ/n973/fG0XokzRYUkRimsPhMDoEERERkajy1ltvhd1/9tlnGTBgAKtXr+bUU08NbV+zZg0PPfQQn332GQMHDgx7zttvv82GDRt45513yM3NZdy4cdx1113ceuutzJ49G4vF0itl6UvU8i0iMa10+3ajQxARERHpFS6XK+ynubk5oufV19cDkJmZGdrW1NTET3/6U+bOndtuY8bKlSs5+uijyc3NDW07++yzcblcrF+//hBL0j91q+V79erV5OTkAFBRUUFeXh4+n4+qqioGDx5MY2MjtbW1DB06lJqaGlwuF8OHD8fpdOJ2uyksLKS0tBSv18uoUaPYsmULfr+fMWPGsGHDBgKBAGPHjmXt2rUA7d42m80UFRWxbt06EhISGDFiBBs3biQpKYmCggKKi4ux2Ww4HA62bt2K3W4nMzOTbdu2kZGRQUpKCmVlZWRnZ2OxWCgvLw8dUCpTeJkGDx1KosVCa3o629evZ/jw4ZSUlBAIBCgsLKS4uBig3dtms5lhw4axdetW4uPjGTx4MCUlJVgSE3E4HJRu347VaiUrK4sdO3Zgs9lIS0ujvLwcu92O1WqloqKC9PR0EhISqKysJDMrC4Ca6mpycnLw+/3U1dWRm5uLx+PB5XKRl5dHfX09breb/Px8qqur8Xg8FAwZgtPpxNfczLBhwygrK6OlpUVl6gNlqq+vZ/369X2qTH3x/2R0mWwFBbQmJZFw1FFs27y5X9XlPVWm+DRbxN8fSkvLoMkX9WUqKChg6NAgcXEJDBxoYf364oiOvaysti+z1dU13f48DRlSgNPppLnZd9g/T4mJFhwOB9u3l3b786QydV2mgQPzsNkSGDTIy6pVX6mOUJl6rExlZWWMGTMGgIEDB9LU1BSqX2fNmsXs2bM7rYMDgQA33HADJ598cuh1AG688UZOOukkpk6d2u7znE5nWOINhO47nc5O31PaZwoGg0Gjg5Ao1dSE6/XXsQ8aBElJRkcj0q76+nrS0tKMDkOindeLa+dO7OeeC8nJRkfTJ+ysrST/lgsj2nfHAy8wKCOnhyM6PJqa4PXXXQwaZNepTzrl9cLOnS7OPdeuakV6jcvlCrufmJhIYhfz31xzzTUsWbKEjz76iPz8fABeffVVbr75Zr744gv+f3t3HhdVuf8B/HOGfREB2U3UUBI3VBQlzcys1DT30uuWeLVUuqW5peYS6jVsUSzz6nWtq7a4ZZrmkrlkqbgLoSAIyiIIioCsc35/8GMCgeEZZOYM8Hm/XrwE5szhe+Qzh/me85zn2NraAgAkScKuXbswcOBAAMDEiRNx69YtHDx4ULOu7Oxs2NjYYP/+/ejTp081blndwGHnpFViYqLSJRBpdfv2baVLoBqC+zMSxayQKGaFDM3Ozq7UR2WNd1BQEH766Sf8+uuvmsYbAI4ePYro6GjY29vD1NQUpqZFA6KHDBmCHj16ACiaVyc5ObnU+oq/5pw7VcPmm7Sy5qFcMnI2NuJDX6lu4/6MRDErJIpZIWMlyzKCgoKwa9cuHD16FE2bNi31+OzZs3H58mVcvHhR8wEAn3/+OTZu3AgACAgIwJUrV3D37l3N8w4dOgQ7Ozu0bNnSYNtSm3C2c9Kqnp2d0iUQacUh5ySK+zMSZWdXT+kSqIZgVshYTZkyBVu3bsWePXtQr149zTXa9evXh5WVFdzc3Mo9e+3p6alp1F9++WW0bNkSo0ePRkhICJKSkjBv3jxMmTKl0jPuVD4231SxYcNgce0a8NRTwMqVSldDVK6EhAQ4ODgoXQYZu1mzYHH7NrBlC7Bvn9LVkBEbNgy4ds2Cf/qoUrNmAbdvW3C3Qkbpq6++AgDNEPJiGzduxJtvvim0DhMTE/z000+YNGkSAgICYGNjg7Fjx+Kjjz6q5mrrDjbfVLGLF2GVkFA0+wyRkbLj2UwScf06rFJSgPx8pSshI3fxIpCQYMU/fVSp69eBlBQr7lbIKFVlTu3yntO4cWPs37+/Okoi8JpvIqrhrKyslC6BiIiIiKhSbL6JqEZ7fBZOIiIiIiJjxOabiGo0e3t7pUsgIiIiIqoUm28iqtHMzMyULoGIiIiIqFJsvomoRktJSVG6BCIiIiKiSrH5JqIazbFBA6VLIKqTrM0toZIqfxuhklSwNrc0QEVERETGjbcao4o5OgJ5eUCDBoApo0LGSWVuznxS5Ro0AGS5aL9G1cLBph5SV+xGTl6O1uUszS3hYFPPQFU9Of7pI1HcrRCRriS5KjeBIyIiIiIiIiJhHHZOREREREREpGdsvkmrsLAwpUsg0ooZJVHMColiVkgUs0JEumDzTVpZWVkpXQKRVswoiWJWSBSzQqKYFSLSBZtv0srNzU3pEoi0YkZJFLNCopgVEsWsEJEu2HyTVtHR0UqXQKQVM0qimBUSxayQKGaFiHTB5pu0srOzU7oEIq2YURLFrJAoZoVEMStEpAs236SVI29eSUaOGSVRzAqJYlZIFLNCRLpg801axcbGKl0CkVbMKIliVkgUs0KimBUi0gWbb9LKwcFB6RKItGJGSRSzQqKYFRLFrBCRLth8k1a2trZKl0CkFTNKopgVEsWskChmhYzV8ePH0b9/f3h4eECSJOzevbvU42+++SYkSSr10bt371LLpKWlYeTIkbCzs4O9vT3Gjx+PzMxMA25F7cPmm7SKj49XugQirZhREsWskChmhUQxK2SssrKy4Ovriy+//LLCZXr37o3ExETNx7Zt20o9PnLkSFy7dg2HDh3CTz/9hOPHj2PixIn6Lr1WM1W6ADJuTk5OSpdApBUzSqKYFRLFrJAoZoWMVZ8+fdCnTx+ty1hYWFR4r/qIiAgcOHAAZ8+eRceOHQEAq1atQt++ffHJJ5/Aw8Oj2muuC9h8k1bm5uZKl1ArnG0XgNykJJ2fZ+Hmhk4XT+uhotqDGSVRzAqJYlZIFLNChpaRkVHqawsLC1hYWFRpXceOHYOLiwscHBzQs2dPLF68GA0aNAAAnD59Gvb29prGGwB69eoFlUqFP//8E4MGDar6RtRhOjXfYWFhcHZ2BgAkJyfDw8MDeXl5SE1NRaNGjZCZmYn09HQ0adIEaWlpyMjIgJeXF5KSkpCVlQVvb2/ExcUhJycHPj4+iIqKQn5+Plq3bo3w8HCo1Wr4+vri0qVLAFDu5yqVCi1btsTVq1dhZmaGZs2aISIiApaWlvD09MT169dhY2MDNzc3REdHw87ODo6OjoiNjYWDgwNsbW0RHx8PJycnmJubIyEhAa6urtymCrYpLy8PKSkptWqblPg95SQkokFOrs4v0NQ7CUhJSTHKbTKW39P58+eRkJBQq7apNv6ejGGbIiIiYG5uXqu2qTb+noxhm+7duwcrK6tatU218fdkDNtUUFCApKSkWrVNtfH3VNO3KT4+Hq1btwYAuLu7Izs7W/NeccGCBVi4cCF01bt3bwwePBhNmzZFdHQ05syZgz59+uD06dMwMTFBUlISXFxcSj3H1NQUjo6OSKrCCSUqIsmyLCtdBBmvuLg4eHp6Kl1GjXfSrSkcs3N0fl6atSW6JcXooaLagxklUcwKiWJWSBSzQoZWlTPfkiRh165dGDhwYIXL3Lx5E15eXjh8+DBefPFFLF26FJs3b0ZkZGSp5VxcXLBo0SJMmjSpyttQl3HCNSIiIiIiohrAzs6u1EdVh5w/7umnn4aTkxOioqIAAG5ubrh7926pZQoKCpCWllbhdeJUOV7zTVolJyfziG4NVheuNWdGSRSzQqKYFRLFrFBtcfv2bdy7dw/u7u4AgICAANy/fx9hYWHw8/MDABw9ehRqtRqdO3dWstQajc03acWZDGu23KSkqg13r0HX8jCjJIpZIVHMColiVshYZWZmas5iA0BMTAwuXrwIR0dHODo6YtGiRRgyZIjm2vWZM2eiWbNmeOWVVwAAPj4+6N27NyZMmIA1a9YgPz8fQUFBGD58OHP/BDjsnLTKy8tTugQirZhREsWskChmhUQxK2Sszp07h/bt26N9+/YAgGnTpqF9+/aYP38+TExMcPnyZbz22mvw9vbG+PHj4efnhxMnTpQaxv6///0PLVq0wIsvvoi+ffuiW7duWLt2rVKbVCvwzDdplZqaiqZNmypdBlGFmFESxayQKGaFRDErZKx69OgBbfNqHzx4sNJ1ODo6YuvWrdVZVp3HM9+kVaNGjZQugUgrZpREMSskilkhUcwKEemCzTdplZmZqXQJRFoxoySKWSFRzAqJYlaISBdsvkmr9PR0pUsg0ooZJVHMColiVkgUs0JEumDzTVo1adJE6RKItGJGSRSzQqKYFRLFrBCRLth8k1ZpaWlKl0CkFTNKopgVEsWskChmhYh0wdnOSauMjAylSyDSihklUcxK9fFe7I2EjASdnuNh54Hr867rqaLqxayQKGaFiHTB5pu08vLyUroEMoA+Q1KQYqX++xsSoJppW+nzjOHNNDNKopiV6pOQkYAssyydn1NTMCskilkhIl2w+SatkpKS4OjoqHQZpGcpVmo8cnj8XpCVv7E2hjfTzCiJYlZIFLNCopgVItIFr/kmrbKydDuzQWRozCiJYlZIFLNCopgVItIFm2/SytvbW+kSiLRiRkkUs0KimBUSxawQkS7YfJNWcXFxSpdApBUzSqKYFRLFrJAoZoWIdMHmm7TKyclRugQirZhREsWskChmhUQxK0SkCzbfpJWPj4/SJRBpxYySKGaFRDErJIpZISJdcLZz0ioqKgrt2rVTugyiCjGjJIpZIVHMColiVojEqNVqSJIESZIAAH/88Qd2796N3NxcvP766wgICKjwuYGBgTr/PEmSsH79+irXqy9svkmr/Px8pUsg0ooZJVHMColiVkgUs0JUudmzZ2P58uVo1aoVLl++jCNHjqB3795Qq9UAgC+++AK//PILXnjhhXKfv2nTJk3TLkKWZaNtvjnsnLRq3bq10iUQacWMkihmhUQxKySKWSGq3KlTpyDLMgYNGgQAWL16NQoLCyHLMmRZRmFhIUJCQrSuo3jZyj6MHZtv0io8PFzpEoi0YkZJFLNCopgVEsWsEFUuKioKkiRpDladOnUKkiThhx9+wIQJEwAA586dq/D5v/76a6mPQ4cOoW3btrC2tsbcuXOxZ88e/Pjjj5gzZw6sra3h7e2NAwcOGGTbdMVh56RV8XAQImPFjJIoZoVEMSskilmpnPdibyRkJOj8PA87D1yfd10PFZGhpaWlAQCcnZ2RlpaGu3fvwt7eHoMHD4a9vT3WrVuHBw8eVPj8559/vtTXH330Ea5cuYJVq1Zh8uTJmu/369cPHh4eeOedd3Ds2DG89NJL+tmgJ8Dmm7Ty9fVVugQirZhREsWskChmhUQxK5VLyEhAlllWlZ5HtYOVlRUePnyIM2fOaBrxFi1aAACysoqyYWdnJ7y+devWAQAaNWpU5rGnnnoKsixj06ZNWLJkyZOWXu047Jy0unTpktIlEGnFjJIoZoVEMSskilkhqlybNm0AAB988AGGDRsGSZLQuXNnAEBcXBwAoGHDhsLru3fvHgBg0aJFiIyM1Hw/MjISwcHBAID09PRqqb26sfkmIiIiIiIivXjvvfcgSZJmUjRzc3NMnDgRALBv3z4AQNeuXYXX5+/vDwC4cOECWrZsCTs7O9jZ2aFly5Y4f/58qebe2HDYOWnF4VRk7JhREsWskChmhUQxK0SVGzJkCI4ePYq9e/fCzMwMI0eOhI+PDwCgR48e6Nq1K/r27Su8vhUrVuCFF17QXCeemZlZ6nE7Ozt8/vnn1bcB1YhnvkkrDqciY8eMkihmhUQxKySKWSES0717dyxfvhxLly5Fq1atNN+fOXMm5s6di/bt2wuvq127djh37hzeeOMN2Nraar5vY2ODN954A+fOnUO7du2qs/xqwzPfREREREREpFd37tzBd999h4iICGRnZ2PDhg34448/AABdunSBubm58Lq8vLywbds2yLKMu3fvAgBcXFwgSZJeaq8ubL5JKw6nImPHjJIoZoVEMSskilkhErNmzRpMnToVeXl5kGUZkiThm2++wbhx4xAbG4tt27bh9ddf13m96enpiI6ORlZWlvCtxbKysmBubg4zMzMARfcd379/PwCgb9++Ol1/risOOyetOJyKjB0zSqKYFRLFrJAoZoWocgcOHMDkyZORm5sLWZZLPTZo0CDIsowdO3botM5bt27h1VdfhYuLC5577jn06dMHOTk5aNWqFby8vBAWFlbhc7t3766ZJf2///0vBg0ahIcPHyIzMxNDhw7F+vXrdd9IQWy+SSuVihEh48aMkihmhUQxKySKWSGq3McffwwAcHd3x+TJk0s9VnwbMl0OZN25cwfPPvssDhw4ALVarZlF3dLSEm3btkVMTAy2b99e4fNv3LiB1q1bAwA+/fRTHDlyBKGhoVi5ciWOHj2KpUuX6rqJwrjHIK1atmypdAlEWjGjJIpZIVHMColiVogqV3z7r5CQEIwYMaLUY0899RSAooZa1MKFC5GYmAhZltGkSZNSj3Xr1g0AcPTo0Qqfb29vr/l56enpeOaZZzSPeXl5ISUlRbgWXbH5Jq2uXr2qdAlEWjGjJIpZIVHMColiVogql5+fDwBo0KBBmcdSU1MBoMxwdG1+/vlnSJKEWbNm4euvvy71WHEzfvv27QqfHxQUhLFjxyImJgbTpk3DlClTcPv2bdy+fRvvvvsuXn75ZeFadMUJ10ir4okIiIwVM0qimBUSxayQqLqcFe/F3kjISKh0uazcLKDu/jcRis4mh4eHY/Xq1Zg6darm+9nZ2QgNDQUAeHt7C6+v+Mx0r169yjxmYmICAJp7gJdn5syZsLGxQbdu3ZCdnY0HDx5gw4YNMDc35zXfpKxmzZopXQKVw3uxN2xn2lb6kZWbpXSpeseMkihmhUQxKySqLmclISMBWWZZlX7AuO/8VGsdP34c/fv3h4eHByRJwu7du0s9Lssy5s+fD3d3d1hZWaFXr164ceNGqWXS0tIwcuRI2NnZwd7eHuPHj0dmZqbOtQwZMgSyLGPfvn3o27ev5vvu7u74448/IEkShg4dKry+4jPo586dK/PYoUOHAACurq5a1zFlyhTEx8fj0qVLOHXqFMLCwnDv3j18/fXXqF+/vnAtutLpzLfLXBdk52cLL+9h54Hr867rXBQZj4iICHTq1EnpMqrN2XYByE1K0vl5Fm5u6HTxtB4qqpriP3iVkSVrA1RTdaJHzR9Xct9S2zJK+sOskChmhUQxK2SssrKy4Ovri8DAQAwePLjM4yEhIQgNDcXmzZvRtGlTfPjhh3jllVcQHh4OS0tLAMDIkSORmJiIQ4cOIT8/H+PGjcPEiROxdetWnWqZMWMGdu7ciatXryI3N1dzL+6HDx8CANq2bVvqjHhlnn/+eXz77beYP39+qduLBQYGYvPmzZAkCS+88EKl61GpVPD09ISnpyeAouvOf/31VyQkJODRo0ewsrKCh4cH2rVrh4YNG+qyyRXSqfnOMstCNsSb76q8qSbjUvziqy1yk5LgmJ2j8/PSqtCwU+VEDyKU97xitS2jpD/MColiVkgUs1J3VMcJA0Pq06cP+vTpU+5jsixjxYoVmDdvHgYMGAAA2LJlC1xdXbF7924MHz4cEREROHDgAM6ePYuOHTsCAFatWoW+ffvik08+gYeHh3AtNjY2OHnyJObMmYNt27YhPT0dAODg4IARI0ZgyZIlsLKyEl7fnDlzsHv3buTl5Wmu/waAzZs3a2Y9nzlzpvD6fv/9d8ycOROnT58u99pzSZLQpUsXhISEPPE9wDnsnLQqPhJEZKyYURLFrJAoZoVEMSt1h+gw+8c/qvtkZEZGRqmP3NxcndcRExODpKSkUtdM169fH507d8bp00UjPU+fPg17e3tN4w0UXWOtUqnw559/6vwz7ezs8MUXXyA1NRXJyclITk5GamoqvvjiC52Hebdp0wY7d+6Ek5OT5jZjxR/Ozs7YsWOH8J0IDh8+jB49eiA5ORlLlizB4cOHce3aNURHR+PatWs4fPgwgoODkZKSgp49e+Lw4cM6b3tJ1Trh2jebHdEg20TztSQDJzY3hSyrAbno1L66nM8tPNxgumE11Go1fH19Nfd5K+9zlUqFli1b4urVqzAzM0OzZs0QEREBS0tLeHp64vr167CxsYGbmxuio6NhZ2cHR0dHxMbGwsHBAba2toiPj4eTkxPMzc2RkJCguSYgOTkZHh4eyMvLQ2pqKho1aoTMzEykp6ejSZMmSEtLQ0ZGBry8vJCUlISsrCx4e3sjLi4OOTk58PHxQVRUFPLz89G6dWuEh4fX+G3Ky8uDjY1NrdkmdaG6StlWF6oRFhZW5W2S1eIzOD7+c1NSUspsk7pQbRSTl8iyjLNnz1b591TV7VAXqnH27Fn4+vri+PHjcHNzM/rs1dZ9RE3apoiICHTp0qVWbZNSvye1Wvd9qawu2l8Y6zaV/D3du3cP/v7+Nf73VBuzZ2zbVFBQAHNzc71s07C9w5DyKAWyWi46syfh789R9De4vM8bWDbAmaAzev896fu9iLpQjTt37hhN9qqy3yvejri4OABVz158fLzmvtTu7u7Izv57JPKCBQuwcOFCnWpK+v8RnY9fF+3q6qp5LCkpCS4uLqUeNzU1haOjo2YZEdnZ2bC1tYVKpcJnn32Gf/3rX3B2dtap3vL06dMHsbGx+OWXX3D9etHIAm9vb7z00kuwtha/7HLevHnw9/fHkSNHYGFhUeZxHx8f9OzZE9OnT8cLL7yAefPmlTvRmyhJ1mFed5uFNlqv+f75K2d4FphU+HhF0qwt0S0pRufnkf6Fh4fXqntYnnRrWrVh50+Y0er+ubYzbYWGa4u+JjuOSsYjB90PENjk2yAzRPeJN4qJboe2n1vbMkr6w6xUn6q8dp90fyGqOoaGMiskSp9ZqY6/kfokXF8WABvd12+o7RBlLL+PjIyMUl9bWFiU2zSWJEkSdu3ahYEDBwIoGmbdtWtXJCQkwN3dXbPc66+/DkmS8O2332Lp0qXYvHkzIiMjS63LxcUFixYtwqRJk4RrdnJyQnp6Og4ePPhEjas+WFtbIzQ0FP/85z8rXXbdunV49913Sx380BVvNVYDGXLSMDc3N51/DpEhMaMkilmpG6pjLglmhUQxK2RodnZ2T7yO4twmJyeXar6Tk5PRrl07zTJ3794t9byCggKkpaXpnPvXXnsNmzdvxunTp6vUfG/ZskXn5wDAmDFjKl3GwcEBUVFRQuuLioqCg4NDlWopxua7BjLkpGHR0dFwdHTU+XlEhsKMkihmhUQxKySKWaGaqGnTpnBzc8ORI0c0zXZGRgb+/PNPzRntgIAA3L9/H2FhYfDz8wMAHD16FGq1Gp07d9bp573zzjs4fvw4Fi9ejPz8fPTr1w+urq6aSyWKVTSHwptvvllm2cpIkiTUfI8aNQqff/45XF1dMWHCBNja2pZZJjMzE2vXrsWKFSvw3nvv6VTH49h8k1bVcXSNSJ+YURLFrFROdGSVekg2YK//epTCrJAoZoWMVWZmZqkzujExMbh48SIcHR3h6emJ9957D4sXL0bz5s01txrz8PDQDE338fFB7969MWHCBKxZswb5+fkICgrC8OHDdZrpHAD8/PwgSRJkWcaSJUuwZMmSMstIkoSCgoIK16HDldI6CQ4ORlxcHN5//33MmjUL3t7ecHd3h4WFBXJzc5GYmIjr16+joKAAw4YNQ3Bw8BP9PDbfpBWP5pKxY0ZJFLNSOeGRVfp5D2Q0mBUSxayQsTp37lype11PmzYNADB27Fhs2rQJM2fORFZWFiZOnIj79++jW7duOHDgQKnb5/3vf/9DUFAQXnzxRahUKgwZMgShoaFPVFdVmugFCxaU+d6uXbtw+fJldO3aFf7+/pAkCX/++SdOnTqF5s2bY+TIkULrNjc3x7Zt2zB16lT88MMPuHjxIhITE0vd57tv374YOnQo/P39da79cWy+SavY2NhqmZGQSF+YURLFrJAoZoVEMStkrHr06KG10ZUkCR999BE++uijCpdxdHTE1q1bn7iW7t276zxsvKTHm+/vv/8eixYtwrRp0/DJJ5+Uemz69On4/PPP0bhxY51+hr+/f7U015Vh8/0EqmNGVWP3pJMKEOkbM0qimBUSxayQKGaFqHLHjh2r1vV99NFHkCSp3MnbevXqhc8++wwhISEYO3Zstf7c6mDUzbchZ/WuiuqYUdXYlTfpAJExYUZJFLNCopgVEsWsEBle8bXs33zzDV5++WWoVCoARUPav/nmGwDAzZs3q/3nPnz4EOnp6RVODCfCqJtvQ87qTeWLj4/nbTTIqDGjJIpZIVHMColiVojE5OXlYefOnTh37hzu378PtVpd6nFJkrB+/XqhdXl5eSEiIgLbtm3Db7/9ppmx/eLFi0hISIAkSfDy8qruTUBoaCjmz5+PwsLCKq/DqJtvUp6Tk5PSJRBpxYySKGaFRDErJIpZIarcvXv38PzzzyMiIqLcx2VZ1qn5nj9/PkaMGAEASEhIQELC36OKi9c1f/78Jy9cD9h8k1bm5uZKl1CnpMtqlDqWlpWNk25NyyxX22/zowtmlEQxKySKWSFRzApR5RYtWoTw8PByH6vKRGyvv/46JEnCtGnTcOfOnVKPNWzYEJ988glef/11oXVt2bJF+OdeuHBBpzrLw+abtEpISEDDhg2VLqPOKATgJKlKf7O8Sy9q+W1+dMGMkihmhUQxKySKWSGq3IEDByBJEkaPHo0tW7ZAkiR89tlnePToEZYsWYL27dtrnXW9PMOGDcOQIUMQFhamub776aefhp+fn+YacBFvvvmm5h7kIp5k1nagljTfomcLH2eoidlEic6eviPXGo4wMUBFgKurq0F+DlFVMaMkilkhUcwKiXo8K1W5E05NugsOUVXEx8cDAN544w3NmeZOnTrh2WefhbW1NaZOnYrff/8dPXr00Gm9KpUKnTp1QqdOnapcm4ODA9q1a4eQkJBKl12/fj3+85//VPlnAbWk+RY+W/gYY5uYTXT2dFmyNkA1RERUW4jePUSdlQ08/veUiIRV5U44NekuOERVYWJSdNLQ1tYWFhYWyMvLQ2JiIgCgefPmkGUZa9aswZw5c4TXWV0TuPn7++Ovv/6Cn59fpcseOHBAuL6K1Irmm/QnOTn5iabTJ9I3ZpRE1eWsiN49JNUAtdQEdTkrpJvamBXRs/dZuVmAmQEKohqvQYMGuH37NrKysuDh4YHY2FjMnz8fycnJ2LBhAwDgwYMHwuurzgnc/P39cfDgQdy9excuLi5al7W3t3/i17sizbfwpFI8Aq84Dw8PpUsg0ooZJVHMComqy1mpyrBpoO4Ona6NWRE+e5+n/1qodvDx8cHt27eRnJyMXr16Yd26dfjrr7/wzjvvACg6S+3v7y+8vuqcwG3mzJkIDAyEg4NDpctOmTIFU6ZM0Wn9j1Ok+RYdJs4j8MrLy+OelYxbVTIqOgT3ccY2T4QSavL/HfdnJKouZ6Uqw6aLn1cX1eWsEIkqnp0cAD788EPs37+/1Czl7u7uCA0NFV5fdU7gZmNjAxsbG9026Alw2DlplZqaiqZNK5+8jkgpVcmo6BDcxxnbPBFKqMn/d9yfkShmhUQxK0SVCwwMRGBgoObriIgI7Nq1C3fu3EHjxo3Rv39/2NraCq9PXxO4GQKbb9KqUaNGSpdApBUzSqKYFRLFrJAoZoVId7a2thg9enSVn6+PCdwMhc03aZWZmal0CVUa5moMQ1zJMIwho1QzMCsKyAbw/7dOzZKzYDuz8jMbxnDtMLNCopgVIjFqtRoHDx5EVFQU7t+/X+59tefPny+0ruqewM2Q2HyTVunp6UqXUKVhrsYwxJUMwxgySjUDs6IAGUCJS+myUPm1xIa6dvibzY5okG2i+VqSgZNbioYPqwvVSDIpmptmRN/buGdVYppYSYLK2qrS9RvDQQTSP+5XiCp3+fJlDBo0CLGxsVqXE22+q3sCN0Ni812L9RmSghSrEve8kwCVjmcdmjRpoqfqiMRpe5MsyzJOVjCz5ZOOgKiO1xAZD+7PqKQG2SbwLDAp/c1yDvTesyzEI/uSZ2hkwIgOIpCyuF+hMkqM+AFq1qgffZk8eTJiYmK0LqPLLOXDhg2r1gncDInNdy2WYqXGI4fHh3To9oYhLS0Nzs7O1VwZkW5E3yQ/7klHQFTHa4iMB/dnVJeJXsKlHpIN2Ou/ntqC+xUq47ERP4BxjfpRQlhYGCRJwlNPPYUpU6agQYMGMDWtehs6fvx4jB8/XvP1k07gZkhsvkmrjIwMpUsQInqGckeuNRxhUub7RFT71ZT9GZE+CF/CVfYyzFrtSeeV4X6FqHLOzs64c+cOQkNDMWDAgCdaV3Z2NoKCggAAAwcOxGuvvfbEE7gZEptv0srLy0vpEoSInqGUJWvDFERERqem7M+IyHCedF4Z7leqEYdr11oTJkzAggULEBUV9cTrsra2xvbt25Gbm4s33nijGqozLDbfpFVSUhIcHR2VLoOI6jjvxd5VGpJX8k2ZPvdnVTl7BvDODEQ1Hd8nVSMO1641jh8/Xurrrl27wsfHB3PnzkVCQgK6d+8OBweHMs/r3r270Pp9fX1x5swZpKWlVUu9hsTmm7TKyqp8p1dVwtefZWUDkkpvdVDtkS6rUVjyG1nZOOnWtMxyzFTNk5CRgCwz3fdHJd+U6XN/VpWzZwDvzFAX8UBN+Yz9/6XU5W0lLm1TF6qhMvn770lWbhZgVsnKBM/wCq2LyAj16NGj3AnUZFnGihUrsGLFijKPSZKEgoICofWHhITglVdewcKFC9GpUyc0a9bsSUs2GDbfhlCDd7Le3t56W7fom9VUvVVAtU0hAKfHm+pyMsZMlVUXDobpc39GJIoHaspn7P8vZS9v+/+DeY+/b8sTWJnoGV6RdREZqfLu463t+7pYsGABHB0dcePGDfj4+KB58+ZwdXUt1fBLkoQjR4488c+qbmy+DaEG72Tj4uLQpk0bpcsgIj2rCwfDuD8jIiLSv7Fjx1b7OouHsrdr1w7Hjh2DJEmQJAmFhYWIjIxEZGSkZllZlnW6dZkhsfkmrXJydD8KTURkjLg/IyIi0r+NGzdW+zp79OgBlUqlacJLnkGvjrPphsLmm7Ty8fFRugQiomrB/Rnp0zebHdEg++9bWUoycHIL55wgqm6ir7XH1fZ5E2qKBw8eYPny5Th//jwKCwvh7++Pd955By4uLpU+t7jJjomJ0XeZesPmm7SKiopCu3btlC6DqM4w9kmHajLuz0ifGmSbwLPApPQ3OecEUbUTfa09rrbPm2BsgoODERwcDEdHR8TGxsLS0hLZ2dno2LEjbt68qVnu8OHD2LhxI86ePQt3d3ehdTdu3FhfZesdm2/SKj8/X+kSiOoUY590qCbj/oyoGvGezERPRJcz+CprKzx7M9xQpVWLs2fPoqCgAAMGDIClpSUAYM2aNYiOjoYkSaWGiicmJmLp0qVYtWpVpeu9cOGC8KzoorcuMyQ236RV69atlS6BiKhacH9GVI0EJ5Mt22Dcx8kvOByfSJcz+BKMc/IwbSIiIiBJEvz9/TXf27Vrl+bzwYMHY+zYsZg3bx6uXLmCgwcPCq33X//6l9Byuty6zJDYfJNW4eHh8PPzU7oMIiIxWs7GPX4/3pJ4No5IPzgcn6huSklJAQA0adIEQNHos7NnzwIAVCoVvvrqKzg7OyM7OxsjRoxAfHy80Hpr0uRq5WHzTVqp1WqlSyAiEqftbNzj9+MtISEjQW8lERER1TWPHj0CAGRmZgIAzpw5g7y8PEiSBF9fXzg7OwMAXF1dAQBmZlr+SJfg5uYGCwsLPVRsGGy+SStfX1+lSyAiUozoBHgcMktERMZk4cKFWLRoUanvPfPMM/jrr78AFN1+8/3338f27duRm5uLV155BatXr9Y0w0/Kw8MDcXFxWL16NZo1a4bly5drHuvZs6fm84SEooPfbm5uQuv94Ycf8Oyzz1ZLjUrgOwXS6tKlS0qXQESkmOIJ8Cr7ICIiMjatWrVCYmKi5uPkyZOax6ZOnYq9e/fi+++/x2+//YaEhAQMHjy42n52r169IMsyDh8+jLZt22Lv3r2ax4YNG6b5/LfffgMAeHl5VdvPNmY8801EVIt5L/YWGlK9I9cajjCpdDkiIiKqGUxNTcs9o/zgwQOsX78eW7du1ZyF3rhxI3x8fPDHH3+gS5cuT/yzFy5ciH379iHpsdFjI0eORKdOnQAAWVlZ+P777yFJEnr16vXEP7MmYPNNWnHYOZFx6jMkBSlWJeZkkABVObf5ycrNAiq/+w9kyboaq6sBBG+TxIMSRERkTDIyMkp9bWFhUeE10Ddu3ICHhwcsLS0REBCAf//73/D09ERYWBjy8/NLNbwtWrSAp6cnTp8+XS3Nd8OGDXHhwgWsWrUK58+fR7169dCrVy+MHz9es8z58+fx6quvAgAGDhyodX2enp6QJElz27Kaqk4337Is4+zZs5prG5KTk+Hh4YG8vDykpqaiUaNGyMzMRHp6Opo0aYK0tDRkZGTAy8sLSUlJUBeqtU7gU2PJwJUrV5CTk4O8vDzY2NggPz8frVu3Rnh4ONRqNXx9fTVD0sv7XKVSoWXLlrh69SrMzMzQrFkzREREwNLSEp6enrh+/XqNmsxNXahGWFhYpdtkY2MDNzc3REdHw87ODo6OjoiNjYWsrtkzM1ak+DXk5OQEc3NzJCQk6PR6qs2vofDwcGRlZcHb2xtxcXHIycmBj48PoqKitL6eRKVYqfHI4fFclb3ND/KqvhnVSV2oxtmzZ3XaR5R8PVX7/kLwNkn6PihR/BpycHCAra0t4uPjq/x6Kvn36fHsoQbtgtSFaqSkpFS6TRW9nmqrx19DQO39m6sLWS66n3DJv7m6vJ7UhbXv/0VdqEZSUpJO+4iSr6eatL/QhbbXUMnPK3o9GctryN3dHdnZ2ZqvFyxYgIULF5ZZrnPnzti0aROeeeYZJCYmYtGiRXjuuedw9epVJCUlwdzcHPb29qWe4+rqWuZM9ZNwdXXF4sWLK3z8ueeew3PPPSe0rtjY2GqqSll1uvmWJEkz7AEoOqJSrGnTsvegLJ6VDwAcHR0rvGVNjScBbdq0AVD0B61du3aah0redqzk/11VPj+pqjn/fyoTlWbbRbbP0dFR87mzszNOqmre/RlFPP4aatiwoeZzkddTbX4NtWzZUvNl8esJQKWvp7+vxqpdVCYqzTbqur9wdHSE6vvamZXHX0Mlhwfq+noqVnL/U5y9kzVoF6QyUcHZ2bnSbQIqeD19r/cSFfEkr6Ga9jdXF5JUeltL5kbk9XSnFv4dUpmoygw11un1xNdQuZ8by9+hxMTEUl9XdNa7T58+ms/btm2Lzp07o3Hjxvjuu+9gZWWl1xqpYsaRIjJaHHZORERERGQc7OzsSn2I3nbL3t4e3t7eiIqKgpubG/Ly8nD//v1SyyQnJwvPOk5Vw+abtOJs50RERERENVtmZiaio6Ph7u4OPz8/mJmZ4ciRI5rHIyMjERcXh4CAAAWrrP3q9LBzqpyqlg5TIyIiIiKqraZPn47+/fujcePGSEhIwIIFC2BiYoIRI0agfv36GD9+PKZNmwZHR0fY2dnhnXfeQUBAQLVMtkYVY/NNWpW8bpWIiIiIiIzf7du3MWLECNy7dw/Ozs7o1q0b/vjjD831/59//jlUKhWGDBmC3NxcvPLKK1i9erXCVdd+bL5Jq6tXr5aacIKIiIiIiIzb9u3btT5uaWmJL7/8El9++aWBKiKA13xTJczMauN9oIiIiIiIiAyLzTdp1axZM6VLICIiIiIiqvHYfJNWERERSpdARERERERU47H5Jq0sLS2VLoGIiIiIiKjGY/NNWnl6eipdAhERERERUY3H5pu0un79utIlEBERERER1XhsvkkrGxsbpUsgIiIiIiKq8dh8k1Zubm5Kl0BERERERFTjsfkmraKjo5UugYiIiIiIqMZj801a2dnZKV0CERERERFRjcfmm7RydHRUugQiIiIiIqIaj803aRUbG6t0CURERERERDUem2/SysHBQekSiIiIiIiIajw236SVra2t0iUQERERERHVeGy+Sav4+HilSyAiIiIiIqrx2HyTVk5OTkqXQEREREREVOOx+SatzM3NlS6BiIiIiIioxmPzTVolJCQoXQIREREREVGNx+abtHJ1dVW6BCIiIiIiohrPVJeFrc2stT5uYm0NqaDyfl4ly5AkyeDLlXmetaXOzynJ2swasplc+YLmAMwEVii4nOj/s7W5NSSR+h5/Hv7+PVfl/1WUytoKEqrn9yu6raL/d2VqeMKsVOe2AtW/vdWRlaoQfQ0ptW9R4v9FNCvCtVXzfoX72/Ip9f8i/nOU2QcJ/z5KrtvI9ivVvb9VKivct1T0fAX+X6p5P/U4Q72Gqn07qjlTjzO2v0O6bIdkbSW0HBk/SZZl3d9ZEhEREREREZEwDjsnIiIiIiIi0jM231ShjIwM2NjYICMjQ+lSiMrFjJIoZoVEMSskilkhIl2x+SatsrOzlS6BSCtmlEQxKySKWSFRzAoR6YLNNxEREREREZGesfkmIiIiIiIi0jM231QhCwsLLFiwABYWFkqXQlQuZpREMSskilkhUcwKEemKtxojIiIiIiIi0jOe+SYiIiIiIiLSMzbfRERERERERHrG5puIiIiIiIhIz9h8ExEREREREekZm2+qFpy3j4hqOrVarfmc+zQiIiKqbmy+6YnExMSgsLAQkiQpXQoRUZWp1WqoVCrExsYiNjaW+zQSxgM1JOL69evYtm0bCgsLlS6FiBTE5puqbPXq1RgzZgzu3r2rdClEZRSfxczIyFC4EjJ2xY33xYsX4efnh1OnTildEtUAcXFxiIqKgiRJpUZNED3u4sWLaNGiBdLS0mBiYgKAB22I6io231Qla9euRVBQEN555x24u7uXeox/UEhpxc3UtWvX0LBhQ6xYsULpkshIFWfl0qVLePbZZzFu3DiMHDmy1DLcp9HjIiMj0b59e/Tr1w/Xrl2DSqViA07lunz5Mrp164bp06djypQpmu8Xj65hbojqFknmuwrS0ebNmxEYGIg9e/agX79+SEtLw7179/Dw4UO0atUKFhYWSpdIhDt37qB///54+PAh4uLiEBISgnfffVfpssgIRUZGwtfXF7Nnz8bChQtRUFCAU6dO4e7du2jatCl8fX1hZmamdJlkJJKSkjBy5EgUFBTA1tYWqampWL9+PVq3bq05mEMEFA0179ixI0aOHImvvvoKarUaGzduRExMDCRJwqRJk+Dh4aF0mURkQKZKF0A1S0REBMaNG4fhw4ejX79+iI6OxltvvYXY2FhkZWXBzs4O3333HXx9fSHLMq+bJEUUFhZi3759ePrppzF9+nScOnUKU6dOBQBNA858EgDk5uZi6dKlsLGxwcsvvwwAGDRoEGJiYpCSkoLU1FTNKJ9mzZopXC0Zg8jISJiammLBggXIyclBaGgoxo8fj//+979o06YNCgsLNUOLqW47duwYMjMz0bZtW9y+fRujR49GQUEBsrKyUFBQgJUrV+LHH39Ejx49eOCGqI7gmW/S2fTp0/Hzzz+jb9++2L59OwYNGoS+ffvC2toaISEhOHPmDC5dulRmODqRIV27dg2RkZEYPHgwCgoKsGLFCsycOROff/45z4BTKadPn0ZoaCju3LmDhIQEtGjRAh999BG8vLxw6NAhTJw4EZMmTcKSJUt40IYAFGUmICAAAHDw4EGEhoYiNTVV04Cr1WpIksSsEJYuXYqvvvoKZmZmaN26Nb788ks4OTmhsLAQkyZNwqFDh3Dt2jU0aNBA6VKJyADYfJOwkkfzZ82ahc8//xyTJ09GSEgIzM3NAQAPHjxAQEAA+vTpg08//ZRvVMkgKjpjUPL7OTk5+PLLLzFjxgxNA56Xl4f9+/fD19cXTZs2NXTZpLCS+Thz5gyCg4NRWFiIVatWwcvLS7NcaGgo5s6di+joaLi4uChVLhmxX375BStXriw1BH3evHkYNGgQ/Pz8lC6PFFDyPdOyZcuwc+dOrFu3Dr6+vpplLl26hJ49e2Lr1q145ZVXlCqViAyIw85JmImJieaPyccff4xnnnkGjRs31jTeAGBubg5bW1vNdd9svEnfihuohIQExMXF4cGDB+jatStsbW2hUqlQUFAAU1NTWFpaYvLkyQCAqVOnQq1W49atW9iwYQP++usvhbeCDKE4Kzk5OTA3N9dMkqVSqeDv748lS5YgLi4OjRs3LrW8jY0NmjZtivr16yu8BaSE6Oho7NmzBxkZGejQoQNeeuklWFlZAYBm/1J8ycLKlSsxceJEeHp64rvvvsPw4cOVLJ0MLD09HQ4ODgAAlUqlec80e/Zs9OrVC8888wyAvy97ys/Ph4uLC9zc3JQsm4gMiM03abV161akpaUhKCgIQOkGPDAwsMzyOTk5sLa2LnXWiEhfZFmGSqXC5cuX0bdvXzRo0ABXrlxBly5d8Nprr2HWrFkwNTXVvEG2srLClClTIMsy3n//fdSvXx9Hjx7lhDd1QHEjHR4ejgULFuDdd99F165dSzXgbdu2RevWrTVnw4v/vXLlCry8vHh/3jro6tWr6N69O1q2bImCggIEBwfjH//4BwIDA/HCCy+U2r+8/PLLKCgowOjRo/HXX3/hwoULaN26tdKbQAYSHh6O9u3b4/3338fSpUshSVKp/UvHjh01yxafmPjhhx9Qv359NGzYUKmyicjA2HxThXbv3o1Ro0YBAPLy8jBt2jQAKHcimfz8fNy7dw8TJkxAdnY23nzzTUOWSnWUJElIS0vD8OHDMWLECEydOhWFhYUIDg7Gzp07ERUVhXXr1sHU1FRz0MjMzAzh4eGws7PD77//Dh8fH6U3gwxApVIhJiYGr732Gm7evImYmBh89dVX6NixI1QqleZMVMnLF27duoX//ve/2LRpE06dOgVra2sFt4AMLTs7G9OnT8fo0aOxcuVKAMDx48fxr3/9C8uXL8ejR4/Qt29fmJqaahqsgwcPIicnB2fOnEGrVq0U3gIylISEBIwdOxYtWrTAihUrIEkSlixZUuHovz/++APffvstNm3ahGPHjsHJycnAFRORUjitIpXr5s2bWLduHaZNm4aQkBDMmDEDy5cvL3fZgoIC7N27FwMGDMDdu3dx6tQpzRlyIn1LSkpCXl4exowZAw8PDzRq1AghISEYPnw4wsLC8N577wEoOmikVquxZ88e7N+/H0eOHGHjXYfk5eXhf//7H9q3b49r164hNzcXgYGBOHfuXLlzU1y9ehXjxo3D1q1bcezYMTZSdZClpSXS0tI0I2NkWUb37t2xceNGPHjwAP/5z38QHh4OoOjgzpkzZ3D48GGcOHGCealD1Go1Dh8+jCZNmmDNmjX48ssvsXz5csydOxdA0UHiktMrxcfH4+eff8avv/6K3377rdQ14ERU+/HMN5XL1NQUHTp0QP/+/dGpUyeYm5trbtU0Y8aMUsuqVCo0b94cY8aMwVtvvVVqGB6RvtnY2KCgoACXL19GmzZtIMsy7O3tMXHiROTk5GDXrl3Yu3cv+vfvD5VKBV9fX4SFhXGYXx1TfF23t7c3fHx8cOnSJfj6+iIwMBAbNmyAn59fqbPerVu3xgcffIBmzZpxMr46SJZlZGZmwtzcHKmpqQCKJtCSJAnt27fHypUr0a9fP2zduhWLFy8GAPj7++PkyZOaa36pblCpVOjWrRvq16+PgIAABAQEQJZlvP322wCgOQNefJCvUaNGmDx5MoKCguDs7Kxw9URkaJztnCqUmpqqGQqVk5ODtWvXYurUqfj3v/+NmTNnAgAyMjKQnZ1darIQ3uOUDOnhw4cYOHAg7OzssHbt2lJvZjIzM/H888/Dz88Pa9euVbBKMgb5+fkwMzMr9XWHDh0AABs2bNBck/nrr7+iZ8+eitRIxmXTpk0IDAzEwYMH8dJLL6GwsBCyLMPU1BTr1q3DnDlzcPnyZbi4uPDvHmnk5+fjm2++wVtvvYUZM2ZgyZIlyM/Pxw8//IAOHTpoJl4jorqHpyapQiWvQbK0tMRbb70FWZYxbdo0qFQqBAUF4bXXXkOfPn0wa9YszbJ8A0KGIssy6tWrh08//RRdunTBggUL8PHHH6NevXoAAFtbW7z66qs4ceIER2NQqca7oKAAZmZmCAsLg5+fHwIDA7F27Vps2bIFv//+Ow4fPsyzUoSRI0fi1KlTGDRoEPbt24fnn39e85izszNcXV1hbW3Nv3tUipmZGUaOHAkAeOuttwAAWVlZWLNmDW7cuKFkaUSkML4TJWEWFhaYNGkSTExMMG3aNHzyySewtLTUTMRGZGiSJKGwsBDt2rXDjh07MHToUDx69AizZ8/WnFmIiYmBm5sbb3tHpZiamiI/Px/m5uY4f/48/P398dxzz8Hc3BwnT55k413HFQ8RNjMzw+zZs5GTk4PevXtjw4YN6NWrFxwcHHD69GlYWFiAAwipPObm5hg9ejTUajUmTJgAe3t7nDx5Eo0aNVK6NCJSEJtv0om5uTn69++PpUuXwsvLC7/++iuv8SZFFZ9xevXVV3HgwAEMHToUN27cgJmZGdzd3bF37178/vvvPDNFZZiZmWnOgAcEBCA+Ph7Hjx9Hy5YtlS6NDKy42b5//z7s7e1LHazz8vLCsmXL0KhRI4wZMwZNmzZFvXr1cOvWLRw6dAj29vbKFU4G93hWtFGpVDh9+jTq1auHU6dOcZJPIuI136SbrKwsvP7664iIiMD169fZeJPRKH5DdPPmTfz000+4cOECXF1dMWbMGDZTpNWKFSswbdo0hIWFoX379kqXQwrZsWMHDh48iIULF2pmOH/cn3/+ievXrwMAunXrxsn46iiRrADATz/9hClTpmDHjh2l7vNNRHUXm+86rPi+pI8r77Y7xRITE/H1119j2rRpbLzJIGRZhizLUKlUyMvLA1A0AqPk48V5fTzT2rJMtY8uWSnp4sWLsLGxQfPmzQ1WKxmH4kzEx8ejW7dumDt3LiZOnKh0WWSEqpKVO3fuQKVSwd3d3UBVEpGxY/NdR5V8E7pq1Spcv34deXl5CA4OhouLi9A62HiTPl24cAHNmzeHra0tAGDv3r34+uuvcevWLQwePBidO3dGjx49AJRtqth01y1PkhWiw4cPIzw8HOHh4QgNDS11wIaoJGaFiJ5U2dOeVOup1WrNm88FCxZg/vz5SElJweHDh+Hv749Tp04JrYeNN+mDLMv47bff4Ofnhy1btgAAjh07hjfeeANOTk5o1aoVdu7ciVmzZmHbtm0AUKaZYnNVN1RHVoh++uknvPfeezh27BgyMjKULoeMGLNCRE+KZ77rsLt372LmzJmYMmUKOnXqhIKCAgwYMAAXLlzAt99+i+eee07pEqkOmz17NlasWIHVq1fj1q1bsLa21tzS7vz581i7di0uXryITz/9FF27dlW4WlISs0JPQpZlBAcHY+HChVi/fj3GjRundElkpJgVInpSPPNdR61fvx7NmzfHtWvXYGdnB6DoTPa+ffvQvn17DB8+HCdPnlS4SqqLCgsLAQDLli3DtGnT8Pbbb2PTpk2wtLTULNOhQwdMnDgRubm5OH/+vFKlksKYFdJV8fkGWZahVqsBFI2GmD9/Pt577z1MmjQJP/zwg5IlkpFgVohIH9h811H9+/dHp06dcPHiRaSmpgKA5o/Lvn374Ofnh+7du+PSpUtKlkl1kImJCfLz8wEAS5cuxcKFCxEfH48LFy4gPT1ds1yHDh3g5eWFffv2aZowqluYFdJF8fX+hw8fxj//+U8MGDAAy5YtQ3Z2NgDgs88+w9tvv41Ro0Zhx44dCldLSmJWiEhf2HzXAcVNdUkuLi7Ytm0bOnTogAkTJiAqKgoqlUpzpPfHH3/E+++/j9atWxu6XKrDivNnZmam+d6cOXMwd+5cbNmyBd98802ppkqtVqNRo0YGr5OUx6yQriRJwu7duzF06FAUFBSgS5cuWLRoEaZNm4YbN24AKLrt3JQpUzBs2DDs2bNH4YpJKcwKEekLr/mu5UreeunKlSsoKCiAi4sLGjZsCABITU1F7969kZOTg927d6NZs2ZlZgMuLCyEiYmJIvVT3VGcu+PHj2Pfvn3Izs5Gw4YNMXv2bABFjdWyZcswbNgwtGvXDikpKdiwYQNOnDiBNm3aKFw9GRKzQroozsuVK1cwcOBAzJgxA2+//TYePXqERo0aIT09Hf3798cnn3yCZs2aASjK0JgxY9CiRQuFqydDYlaISN945rsWK9l4z58/HwMHDsTQoUPRokULbNq0Cenp6XBycsLBgwdhZWWFIUOG4K+//iozGzAbb9K34jc8O3fuRL9+/ZCWlgYA+PLLL9GzZ08ARcOKFy1ahO+//x4bN26Eq6sr/vjjDzZTdQyzQqJSU1Nx//59SJKEwsJCpKamYvTo0Xj77bdx+/ZttGzZEmPGjMHp06dx8OBBLFu2DBEREQCKMsRmqu5gVojIYGSq9RYtWiS7u7vLv/zyiyzLsjxq1CjZzs5ODgkJkdPT02VZluXU1FTZ09NTHjVqlIKVUl1RWFhY5ntxcXFyixYt5FWrVsmyLMs3b96UnZ2d5QkTJshqtVqz3KxZs2RXV1c5IyPDYPWScpgVqoobN27ITZs2ld966y357t27sizL8r179+TLly/LBQUF8uDBg+WxY8fKjx49kgsLC+WOHTvKkiTJI0eOlPPy8hSungyJWSEiQ+KZ71ro9OnTuH79OgDg6tWrOHHiBNauXYuXXnoJe/bswb59+/DCCy9g1qxZWLduHe7du4cGDRrg8uXL2LRpk7LFU61XPCLj/PnzCA4O1ly7m5aWBkmSEBQUhPj4eHTv3h2DBw/G2rVrIUkSfvnlFwBFM1tfvnwZ9erVU3IzyACYFaoKtVqNr7/+GrGxsYiKisLixYuRnJwMR0dHtGnTBo8ePUJCQgK6d++umRm/W7du+Pnnn/Hhhx+WmkeAajdmhYgMjc13LRMbG4upU6dixowZuHnzJpo3b47hw4fj5ZdfxokTJzB58mR89NFH2L17N4YNG4alS5ciNDQUDx8+RP369WFiYsLZgElvipupy5cvo1OnTnjw4IHmMof69evD0dERP/30E7p164ZXX30VX3zxBQAgIiICX3/9Nc6cOQMAcHZ2VmwbyDCYFaoqlUqFQYMGoX79+pAkCZGRkVi2bJnmzh5ZWVmIiYnB+fPncfbsWcybNw87duxA586d8cwzzyhcPRkSs0JEhsYJ12qhdevWYfv27XBycsKnn36Kp556CgAwceJEFBQU4D//+Q/MzMzwzjvv4NSpU7C2tsaJEyfKXOtNVJ2Km6lLly4hICAAU6dOxZIlSzSPP3z4EL1798aZM2cwYsQIbNmyRfPY9OnT8eeff2LHjh1wcXFRonwyIGaFqkr+/3sym5iYYP78+cjOzoa1tTX279+P5557DrNnz4arqyv27t2LIUOGoFGjRsjNzcXevXvRvn17pcsnA2JWiEgJpkoXQNVH/v+JiCZMmAAzMzNs2LAB77//PoKDg+Ht7Y3IyEi0adNGM0zqzp072LhxI9q2bQtJksrMck5UnVQqFaKiotClSxdMnz5dM4xYkiRs2bIFnTt3RmhoKHr06IG8vDzs3LkTLi4u+P7777F582YcP36czVQdwayQrtLS0jR38yieaLRx48ZYt24dDh8+jAYNGuCbb77BsmXLMHv2bPTv3x+RkZHIyMiAq6sr3NzcFN4CMhRmhYiUxGHntUhxAw0Ab775JgIDA5GcnIwPP/wQ9+7dw+uvv46vvvoK//jHP9ChQwdERkaiVatWbLzJINRqNTZs2IB69eqhQYMGAIoyu3jxYrz//vtIT0+Hn58f9uzZg/j4eAQFBeHtt99GWFgYfvvtN7Rt21bhLSBDYVZIFzdu3IC/vz969uyJH3/8UTPnyfjx42FtbY3g4GC8++67GDBgAH7//XcsX74ciYmJaNq0KXx9fdlM1SHMChEpjWe+a5mSjfSbb74JAFi/fj2mTJmCFStWwMzMDEeOHIG/vz9WrVoFU1NT3sebDEKlUiEoKAjZ2dnYvn07LC0tkZGRgdDQUGzZsgVdunSBWq1Gz5490aFDB2RkZMDExAT16tWDnZ2d0uWTATErJEqtVmPTpk1ISkpCvXr1sHDhQjRr1gxOTk74+OOPMWrUKJw8eRJ5eXmYN2+eZvSEhYUFgoODNWc+qfZjVojIGPCa71qq5JnsjRs3YsOGDWjYsCFWrlwJV1dXzTWVBQUFMDXlMRgynKSkJCxZsgSHDh1CdHQ0Dh48iJ49e/IgEJXBrJCIxMREfPzxx7h16xYcHR0xYsQIfPDBB/Dw8EBWVhaOHj2K9evXY9y4cQCATz75BEOHDkWTJk2ULZwMjlkhIqXxMF4tVXII+rhx4xAYGIiEhATMmDEDt2/fhkqlgizLbLzJ4Nzc3DBv3jy88soraNmyJS5cuAAAnGmfymBWSIS7uztmzpyJhg0b4q+//kJUVBTOnj2Lt956C+3atQOAUrebmz59OpupOopZISKl8cx3LVfyDPiGDRuwdu1aTJw4EYGBgbzOmxRVfFbz7NmzGDRoEGbNmgXg75muiYoxKyQiMTERS5cuxenTpzFq1Ci89957AICbN2/i6aefVrY4MirMChEphc13HVCyye7Xrx9MTU2xe/duZYsiwt9N1YULF/Diiy9i0aJFSpdERopZIRHFOTlz5gwGDBiAOXPmAAAvVaAymBUiUgJPGdQBJYegN27cGFZWVsjLy1O4KqKiYcVz585F8+bN8fvvv+PevXtKl0RGilkhEcU58ff3x/79+7FgwQIAYDNFZTArRKQEnvmuQ1JTUzFw4ECsWbMGrVu3VrocIo3k5GQAgKurq8KVkLFjVkhEUlISPvjgA9y+fRvbt2/X3LKO6HHMChEZEpvvOiYnJweWlpZKl0FERKRXPFBDopgVIjIUNt9EREREREREesZrvomIiIiIiIj0jM03ERERERERkZ6x+SYiIiIiIiLSMzbfRERERERERHrG5puIiIiIiIhIz9h8ExEREREREekZm28iIiIiIiIiPWPzTURERERERKRnbL6JiIiIiIiI9IzNNxEREREREZGesfkmIiIiIiIi0rP/Azo7z9bHgcWcAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import yfinance as yf\n",
    "import mplfinance as mpf\n",
    "import pandas as pd\n",
    "\n",
    "# Download the stock data\n",
    "df = yf.download('TSLA', start='2022-01-01', end='2022-03-31')\n",
    "\n",
    "# Define the date ranges for shading\n",
    "red_range = ['2022-01-15', '2022-02-15']\n",
    "blue_range = ['2022-03-01', '2022-03-15']\n",
    "\n",
    "\n",
    "# Create a function to shade the chart regions\n",
    "def shade_region(ax, region_dates, color):\n",
    "    region_dates.sort()\n",
    "\n",
    "    start_date = region_dates[0]\n",
    "    end_date = region_dates[1]\n",
    "\n",
    "    # plot vertical lines\n",
    "    ax.axvline(pd.to_datetime(start_date), color=color, linestyle='--')\n",
    "    ax.axvline(pd.to_datetime(end_date), color=color, linestyle='--')\n",
    "\n",
    "    # create fill\n",
    "    xmin, xmax = ax.get_xlim()\n",
    "    ymin, ymax = ax.get_ylim()\n",
    "    ax.fill_between(pd.date_range(start=start_date, end=end_date), ymin, ymax, alpha=0.2, color=color)\n",
    "    ax.set_xlim(xmin, xmax)\n",
    "    ax.set_ylim(ymin, ymax)\n",
    "\n",
    "\n",
    "# Plot the candlestick chart with volume\n",
    "fig, axlist = mpf.plot(df, type='candle', volume=True, style='charles', \n",
    "                        title='TSLA Stock Price', ylabel='Price ($)', ylabel_lower='Shares\\nTraded', \n",
    "                        figratio=(2,1), figsize=(10,5), tight_layout=True, returnfig=True, show_nontrading=True)\n",
    "\n",
    "# Get the current axis object\n",
    "ax = axlist[0]\n",
    "\n",
    "# Shade the regions on the chart\n",
    "shade_region(ax, red_range, 'red')\n",
    "shade_region(ax, blue_range, 'blue')\n",
    "\n",
    "\n",
    "# Show the plot\n",
    "mpf.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "red_range = ['2022-01-15', '2022-02-15']\n",
    "blue_range = ['2022-03-01', '2022-03-15']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = df.Volume.values\n",
    "shift = 0.75*min(y)\n",
    "y = [y-shift for y in y]\n",
    "x = [x for x in range(len(y))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 61 artists>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 61 artists>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1100x850 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2,figsize=(11,8.5),facecolor='k',tight_layout=True)\n",
    "ax[0].set_facecolor('k')\n",
    "ax[0].bar(x,y,width=1,color=('r','g'))\n",
    "ax[1].set_facecolor('w')\n",
    "ax[1].bar(x,y,width=1,color=('r','g'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mplfinance._helpers as h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = ['r','g']\n",
    "newcolors = h._adjust_color_brightness(colors,amount=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1.0, 0.0, 0.0), (0.0, 0.5, 0.0), 'r', 'g', 'r', 'g']"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newcolors = newcolors + colors\n",
    "newcolors + colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 61 artists>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 61 artists>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1100x850 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2,figsize=(11,8.5),facecolor='k',tight_layout=True)\n",
    "ax[0].set_facecolor('k')\n",
    "ax[0].bar(x,y,width=1,color=newcolors)\n",
    "ax[1].set_facecolor('w')\n",
    "ax[1].bar(x,y,width=1,color=newcolors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "def adjust_color_brightness(color,amount=0.5):\n",
    "    \n",
    "    def _adjcb(c1, amount):\n",
    "        import matplotlib.colors as mc\n",
    "        import colorsys\n",
    "        # mc.is_color_like(value)\n",
    "        try:\n",
    "            c = mc.cnames[c1]\n",
    "        except:\n",
    "            c = c1\n",
    "        c = colorsys.rgb_to_hls(*mc.to_rgb(c))\n",
    "        return colorsys.hls_to_rgb(c[0], max(0, min(1, amount * c[1])), c[2])\n",
    "\n",
    "    if not isinstance(color,(list,tuple)):\n",
    "        return _adjcb(color,amount)\n",
    "        \n",
    "    cout = []\n",
    "    cadj = {}\n",
    "    for c1 in color:\n",
    "        if c1 in cadj:\n",
    "            cout.append(cadj[c1])\n",
    "        else:\n",
    "            newc = _adjcb(c1,amount)\n",
    "            cadj[c1] = newc\n",
    "            cout.append(cadj[c1])\n",
    "    return cout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.colors as mc\n",
    "import colorsys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#FF0000'"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mc.cnames['red']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AsinhNorm',\n",
       " 'BASE_COLORS',\n",
       " 'BoundaryNorm',\n",
       " 'CSS4_COLORS',\n",
       " 'CenteredNorm',\n",
       " 'ColorConverter',\n",
       " 'ColorSequenceRegistry',\n",
       " 'Colormap',\n",
       " 'FuncNorm',\n",
       " 'Image',\n",
       " 'LightSource',\n",
       " 'LinearSegmentedColormap',\n",
       " 'ListedColormap',\n",
       " 'LogNorm',\n",
       " 'Mapping',\n",
       " 'NoNorm',\n",
       " 'Normalize',\n",
       " 'Number',\n",
       " 'PngInfo',\n",
       " 'PowerNorm',\n",
       " 'Sequence',\n",
       " 'Sized',\n",
       " 'SymLogNorm',\n",
       " 'TABLEAU_COLORS',\n",
       " 'TwoSlopeNorm',\n",
       " 'XKCD_COLORS',\n",
       " '_ColorMapping',\n",
       " '_REPR_PNG_SIZE',\n",
       " '__builtins__',\n",
       " '__cached__',\n",
       " '__doc__',\n",
       " '__file__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__spec__',\n",
       " '_api',\n",
       " '_check_color_like',\n",
       " '_cm',\n",
       " '_color_sequences',\n",
       " '_colors_full_map',\n",
       " '_create_empty_object_of_class',\n",
       " '_create_lookup_table',\n",
       " '_has_alpha_channel',\n",
       " '_is_nth_color',\n",
       " '_make_norm_from_scale',\n",
       " '_picklable_norm_constructor',\n",
       " '_sanitize_extrema',\n",
       " '_to_rgba_no_colorcycle',\n",
       " '_vector_magnitude',\n",
       " 'base64',\n",
       " 'cbook',\n",
       " 'cnames',\n",
       " 'colorConverter',\n",
       " 'from_levels_and_colors',\n",
       " 'functools',\n",
       " 'get_named_colors_mapping',\n",
       " 'hex2color',\n",
       " 'hexColorPattern',\n",
       " 'hsv_to_rgb',\n",
       " 'importlib',\n",
       " 'inspect',\n",
       " 'io',\n",
       " 'is_color_like',\n",
       " 'itertools',\n",
       " 'make_norm_from_scale',\n",
       " 'mpl',\n",
       " 'np',\n",
       " 're',\n",
       " 'rgb2hex',\n",
       " 'rgb_to_hsv',\n",
       " 'same_color',\n",
       " 'scale',\n",
       " 'to_hex',\n",
       " 'to_rgb',\n",
       " 'to_rgba',\n",
       " 'to_rgba_array']"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(mc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.0, 0.0, 0.0)"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mc.hex2color('red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.6, 0.6, 0.6]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#c = [int(v*255) for v in mc.to_rgb('blue')]\n",
    "adj = 0.6\n",
    "c = [min(1.0,v+adj) for v in mc.to_rgb('k')]\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_color(c):\n",
    "    fig, ax = plt.subplots(figsize=(1.2,0.6),facecolor='k')\n",
    "    ax.set_axis_off()\n",
    "    ax.bar([0],[1],color=c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.5490196078431373, 0.33725490196078434, 0.29411764705882354] \n",
      "\n",
      "[0.7490196078431373, 0.5372549019607844, 0.49411764705882355] \n",
      "\n",
      "[0.9490196078431373, 0.7372549019607844, 0.6941176470588235] \n",
      "\n",
      "[1.0, 0.8372549019607843, 0.7941176470588236] \n",
      "\n",
      "[1.0, 0.9372549019607843, 0.8941176470588235] \n",
      "\n",
      "[1.0, 1.0, 0.9941176470588236] \n",
      "\n",
      "[1.0, 1.0, 1.0] \n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAA0UlEQVR4nO3dsQnDAAwAQTl4O/eZJGN4EveZL9nBCRg/d71A8KjWMjOf4dYeVy/A70QMEDFAxAARA0QMEDFAxAARA0QMEDFgPTu4P7d/7sHMvI73qTmXGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBIgaIGCBigIgBy/iLcXsuMUDEABEDRAwQMUDEABEDRAwQMeAL1dgFg9CxJGcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAA0ElEQVR4nO3dsQnDAAwAQTl4MU+VLoU7T5XRkh2cgPFz1wsEj2otM/MZbu1x9QL8TsQAEQNEDBAxQMQAEQNEDBAxQMQAEQPWs4Pv4/XPPZiZ7bmfmnOJASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBiwjL8Yt+cSA0QMEDFAxAARA0QMEDFAxAARA76hGwWDb+QhhQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAA0ElEQVR4nO3dsQnDAAwAQTm49lTpM6t7T5UFkh2cgPFz1wsEj2otM/MZbu1x9QL8TsQAEQNEDBAxQMQAEQNEDBAxQMQAEQPWs4PvY//nHszM9nydmnOJASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBiwjL8Yt+cSA0QMEDFAxAARA0QMEDFAxAARA75sXgWDWtmu1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAAz0lEQVR4nO3dsQnDUAxAQX2TadJ7/wHcZx1nBydg/LjrBYKHaq2ZOYdH2+5egN+JGCBigIgBIgaIGCBigIgBIgaIGCBiwOvq4Pk5/rkHM7Pe+6U5lxggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIAWv8xXg8lxggYoCIASIGiBggYoCIASIGiBjwBcKyBYNA21ceAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAAz0lEQVR4nO3dsQnDUAxAQX2TBdJ7/8ncZwRnBydg/LjrBYKHaq2ZOYdH2+5egN+JGCBigIgBIgaIGCBigIgBIgaIGCBiwOvq4Pk5/rkHM7Pe+6U5lxggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIASIGiBggYoCIAWv8xXg8lxggYoCIASIGiBggYoCIASIGiBjwBQUpBYPxZVzoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAAyUlEQVR4nO3dQQrDMBAEwZXJ/58c+Q9yILipugsWmjlrzcweXu369wE8J2KAiAEiBogYIGKAiAEiBogYIGKAiAGf04d7f395BzOz1tmmLDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA0QMEDFAxAARA9b4F+P1LDFAxAARA0QMEDFAxAARA0QMEDHgBjzxBYMFlR0AAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHEAAABCCAYAAABgkDnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAAyElEQVR4nO3dMQrDQAwAQcnk/18+/8EJBC8zveBgUaPmdmbO8GrXvx/A90QMEDFAxAARA0QMEDFAxAARA0QMEDHg83TwHCfXX9vdR3M2MUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDRAwQMUDEABEDdvyL8Xo2MUDEABEDRAwQMUDEABEDRAwQMeAGPkUFg/e/tbwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 120x60 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color = mc.to_rgb('orange')\n",
    "color = mc.to_rgb('lime')\n",
    "color = mc.to_rgb('cyan')\n",
    "color = mc.to_rgb('#7f7f7f')\n",
    "color = mc.to_rgb('#bcbd22')\n",
    "color = mc.to_rgb('#8c564b')\n",
    "for adj in [0,0.2,0.4,0.5,0.6,0.7,0.8]:\n",
    "    c = [min(1.0,v+adj) for v in color]\n",
    "    print(c,'\\n')\n",
    "    plot_color(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
